[Senate Hearing 118-66]
[From the U.S. Government Publishing Office]


                                                         S. Hrg. 118-66

                ARTIFICIAL INTELLIGENCE AND INTELLECTUAL
                      PROPERTY--PART II: COPYRIGHT

=======================================================================

                                HEARING

                               BEFORE THE

                 SUBCOMMITTEE ON INTELLECTUAL PROPERTY

                                 OF THE

                       COMMITTEE ON THE JUDICIARY
                          UNITED STATES SENATE

                    ONE HUNDRED EIGHTEENTH CONGRESS

                             FIRST SESSION
                               __________

                             JULY 12, 2023
                               __________

                          Serial No. J-118-25
                               __________

         Printed for the use of the Committee on the Judiciary
         

                  [GRAPHIC NOT AVAILABLE IN TIFF FORMAT]
                  

                    U.S. GOVERNMENT PUBLISHING OFFICE
                    
53-116 PDF                 WASHINGTON : 2024                     
                  
         

                       COMMITTEE ON THE JUDICIARY

                   RICHARD J. DURBIN, Illinois, Chair
DIANNE FEINSTEIN, California         LINDSEY O. GRAHAM, South Carolina, 
SHELDON WHITEHOUSE, Rhode Island             Ranking Member
AMY KLOBUCHAR, Minnesota             CHARLES E. GRASSLEY, Iowa
CHRISTOPHER A. COONS, Delaware       JOHN CORNYN, Texas
RICHARD BLUMENTHAL, Connecticut      MICHAEL S. LEE, Utah
MAZIE K. HIRONO, Hawaii              TED CRUZ, Texas
CORY A. BOOKER, New Jersey           JOSH HAWLEY, Missouri
ALEX PADILLA, California             TOM COTTON, Arkansas
JON OSSOFF, Georgia                  JOHN KENNEDY, Louisiana
PETER WELCH, Vermont                 THOM TILLIS, North Carolina
                                     MARSHA BLACKBURN, Tennessee
             Joseph Zogby, Chief Counsel and Staff Director
      Katherine Nikas, Republican Chief Counsel and Staff Director

                 Subcommittee on Intellectual Property

                 CHRISTOPHER A. COONS, Delaware, Chair
MAZIE K. HIRONO, Hawaii              THOM TILLIS, North Carolina, 
ALEX PADILLA, California                 Ranking Member
JON OSSOFF, Georgia                  JOHN CORNYN, Texas
PETER WELCH, Vermont                 TOM COTTON, Arkansas
                                     MARSHA BLACKBURN, Tennessee
                 James Barton, Democratic Chief Counsel
               Seth Williford, Republican General Counsel

                            C O N T E N T S

                              ----------                              

                        JULY 12, 2023, 3:03 P.M.

                    STATEMENTS OF COMMITTEE MEMBERS

                                                                   Page

Coons, Hon. Christopher A., a U.S. Senator from the State of 
  Delaware.......................................................     1
Tillis, Hon. Thom, a U.S. Senator from the State of North 
  Carolina.......................................................     3

                               WITNESSES

Witness List.....................................................    33
Brooks, Ben, head of public policy, Stability AI, San Francisco, 
  California.....................................................     5
    prepared statement...........................................    34
Harleston, Jeffrey, general counsel and executive vice president, 
  business and legal affairs, Universal Music Group, Santa 
  Monica, California.............................................    12
    prepared statement...........................................    45
Ortiz, Karla, concept artist, illustrator, and fine artist, San 
  Francisco, California..........................................    10
    prepared statement...........................................    51
Rao, Dana, executive vice president, general counsel, and chief 
  trust officer, Adobe, Inc., San Jose, California...............     7
    prepared statement...........................................    63
Sag, Matthew, professor of law, artificial intelligence, machine 
  learning, and data science, Emory University School of Law, 
  Atlanta, Georgia...............................................     9
    prepared statement...........................................    71

                               QUESTIONS

Questions submitted to Ben Brooks by Senator Tillis..............    98
Questions submitted to Jeffrey Harleston by Senator Tillis.......   104
Questions submitted to Karla Ortiz by Senator Tillis.............   110
Questions submitted to Dana Rao by Senator Tillis................   115
Questions submitted to Matthew Sag by Senator Tillis.............   121

                                ANSWERS

Responses of Ben Brooks to questions submitted by Senator Tillis.   128
Responses of Jeffrey Harleston to questions submitted by Senator 
  Tillis.........................................................   138
Responses of Karla Ortiz to questions submitted by Senator Tillis   151
Responses of Dana Rao to questions submitted by Senator Tillis...   161
Responses of Matthew Sag to questions submitted by Senator Tillis   171

                MISCELLANEOUS SUBMISSIONS FOR THE RECORD

Submitted by Chair Coons:

    Computer and Communications Industry Association (CCIA), 
      letter, July 12, 2023......................................   192
    Copyright Alliance, letter, July 17, 2023, and attachment....   195
    Digital Media Association (DiMA), letter, July 12, 2023......   201
    Motion Picture Association (MPA), statement..................   203
    Screen Actors Guild-American Federation of Television and 
      Radio Artists (SAG-AFTRA), statement.......................   211
    Songwriters Guild of America (SGA), et al., letter, July 18, 
      2023.......................................................   214


 
                        ARTIFICIAL INTELLIGENCE
                            AND INTELLECTUAL
                      PROPERTY--PART II: COPYRIGHT

                              ----------                              


                        WEDNESDAY, JULY 12, 2023

                      United States Senate,
             Subcommittee on Intellectual Property,
                                Committee on the Judiciary,
                                                    Washington, DC.
    The Subcommittee met, pursuant to notice, at 3:03 p.m., in 
Room 226, Dirksen Senate Office Building, Hon. Christopher A. 
Coons, Chair of the Subcommittee, presiding.
    Present: Senators Coons [presiding], Klobuchar, Hirono, 
Padilla, Tillis, and Blackburn.
    Also present: Chair Durbin.

        OPENING STATEMENT OF HON. CHRISTOPHER A. COONS,
           A U.S. SENATOR FROM THE STATE OF DELAWARE

    Chair Coons. This hearing will come to order. I'd like to 
thank all of our witnesses for participating today, and I'd 
like to especially thank my friend and colleague, Ranking 
Member Thom Tillis and his staff for working with us on such a 
collaborative basis to put this hearing together.
    Welcome back from Vilnius. Senator Tillis was over at the 
NATO summit, and I am thrilled he is able to join us, and we 
are able to do this hearing today. This is our second hearing 
in as many months on the intersection of artificial 
intelligence and intellectual property law and policy.
    You and your team have been great partners in pursuing 
this. If you will indulge me for a moment, Senator, and before 
I proceed with my remarks, I'd like to ask that we play just a 
little clip of something to frame the challenges of this 
topic--made with the permission of all the relevant rights 
holders.
    [Laughter.]
    [Video is shown.]
    Chair Coons. Thank you for your forbearance. Yes, a round 
of applause is certainly welcomed.
    [Applause.]
    Chair Coons. My team actually produced a version of that 
where it is a duet between me and Frank Sinatra, but my voice 
came out so horribly flat, I didn't want to impose that on any 
of you.
    Senator Tillis. Thank you, Mr. Chair, for your judgment.
    [Laughter.]
    Chair Coons. Creating the song, ``AI, AI'' to the tune of 
``New York, New York'' was great fun and I appreciate my team 
that worked so hard on pulling that off, but the very existence 
of it highlights a couple of the core questions around 
copyright raised by generative artificial intelligence.
    ChatGPT wrote the lyrics following the style of ``New York, 
New York,'' although perhaps not quite as moving and inspiring 
as the original words to any but IP enthusiasts. Another 
generative AI tool was used to take Mr. Sinatra's recorded 
songs and his voice and his phrasing and his style and set that 
to music.
    So, a couple of those core questions: Did ChatGPT infringe 
the copyright on ``New York, New York'' when it drafted lyrics 
representing its lyrical style? What about the AI tool that set 
those lyrics to music? Did either that tool or did I run afoul 
of Mr. Sinatra's rights by mimicking his voice?
    In my case, no, because we got specific approval. Or did I 
just use AI tools to enhance my own creativity? And if so, 
should this newly created song be entitled to copyright 
protection? These are just a few of the questions I hope we 
will explore with our panel of talented and insightful 
witnesses as we consider the impact of artificial intelligence 
on copyright law and policy and the creative community.
    As we all know, AI is rapidly developing. Generative AI 
tools have brought many new people into the creative fold and 
have opened new avenues for innovation. People who may not have 
ever considered themselves creatives are now using these tools 
to produce new works of art. Artists themselves have used AI 
tools to enhance their own creativity.
    Paul McCartney recently made headlines announcing that AI 
helped create the very last Beatles song 50 years after the 
band broke up. As I have previewed, AI creates new copyright 
law issues, including whether using copyrighted content to 
train AI models is copyright infringement, whether AI-generated 
content should be given copyright protection, and many more.
    These questions are working their way through the courts. 
How the courts decide them, and the decisions we make here in 
the Senate and in Congress about how to respect and reinforce 
existing copyright protections and works will have significant 
consequences, not just for the creative community, but our 
overall competitiveness as a country. While generative AI 
models are trained on copyrighted content, IP considerations 
haven't been included or sufficiently considered in proposed IP 
regulatory frameworks here in the U.S.
    In contrast, some of our competitors recognize IP policy as 
an important tool. The EU is currently planning to require AI 
companies to publish the copyrighted materials used in training 
models. The UK provides copyright protection for computer-
generated works. These are just some initial concerns, and I 
think there are initial steps that we can take to ensure 
sustained U.S. leadership on artificial intelligence.
    First, it is critical to include IP considerations in any 
regulatory framework for artificial intelligence and to give 
our Copyright Office, in this framework, a seat at the table. 
We should also consider whether changes to our copyright laws 
or whole new protections like a Federal right of publicity may 
be necessary to strike the right balance between creators' 
rights and AI's ability to enhance innovation and creativity.
    I am excited to explore these issues today. We have got a 
great panel, and great partner, and great Members of the 
Committee. With Senator Tillis' cooperation, we have assembled 
this wonderful panel. I will introduce them shortly, but first 
I will turn it over to my Ranking Member, Senator Thom Tillis.

             OPENING STATEMENT OF HON. THOM TILLIS,
        A U.S. SENATOR FROM THE STATE OF NORTH CAROLINA

    Senator Tillis. Thank you, Mr. Chairman, and thanks for 
everyone here. It is great to see the number of participants in 
the audience. It is even more amazing to see an equal number 
who would like to get in here, but who says AI and IP can't be 
sexy?
    But, you know, in all seriousness, I appreciate that we are 
having another hearing on the opportunity to highlight the 
importance of intellectual property when it comes to emerging 
technologies, and today we are talking about AI. During our 
last hearing, we really discussed the impact of AI on patent--
in a patent context, which explored ideas such as whether or 
not AI can be considered an inventor.
    And it cannot, and hopefully it will not in the future. But 
while many of these issues we discussed in the last hearing 
were perspective, the creative community is experiencing 
immediate and acute challenges due to the impact generative AI 
in a copyright context.
    Strong, reliable, predictable IP rights are paramount to 
incentivizing U.S. innovation and creativity. It is this 
innovation and creativity that fuels growth of our country's 
prosperity and drives enormous economic growth. In fact, core 
copyright industries added $1.8 trillion of value to U.S. GDP, 
accounting for almost 8 percent of the U.S. economy.
    These copyright industries also employ 9.6 million American 
workers. The sales of major U.S. copyright products overseas in 
markets also constitute $230 billion and outpaced exports of 
other major U.S. industries. Advances in generative AI have 
raised new questions regarding how copyright principles such as 
authorship, infringement, and fair use will apply to content 
created or used by AI.
    We must not only consider how our current IP laws apply to 
the field of generative AI, but also what changes, if any, may 
be necessary to incentivize future AI innovators and creators.
    So, Chairman Coons, I am happy to have this Committee. I 
will submit the remainder of my statement for the record. But 
for those of you who have watched our Committee over the past 
several Congresses where either Senator Coons or I were in 
Ranking Member or Chairmanship, I think if anything, I hope 
people understand that we are very thorough and we are very 
persistent in our approach, and we are inclusive.
    I have told everyone on this issue, whichever end of the 
spectrum you are, if you are at the table and the work groups, 
we are going to find a reasonable solution and compromises. If 
you are outside of the work group process and you are just 
taking shots at it, you may find yourself on the table, from my 
perspective.
    So, we encourage you to get to the table and make what we 
are doing better. The reason why I think it is so important, 
and I am glad the IP Subcommittee is leading on this in terms 
of formal hearings with a focus on potentially drafting 
legislation, is I think we run the risk of some in Congress who 
think AI is bad--that it's a threat to the future.
    I am not in that camp. I think that AI is good. It is 
something that I first developed expertise in back in the late 
80s, and have followed it every sense. It is a matter of 
getting the regulatory construct, the intellectual property 
construct, all the other underlying policies that you need when 
a new, I think positive--in a positive term, disruptive 
technology hits the field.
    So, the reason that we need to move forward, address 
potential concerns is precisely because I want the United 
States to lead in innovation. And so much innovation is going 
to be premised on properly exploiting the capabilities 
responsibly, and that is what I hope we learn in this hearing 
and subsequent hearings and work group. So, thank you all for 
being here. And thank you, Mr. Chair, for having the hearing.
    Chair Coons. Thank you, Senator Tillis. I am now going to 
turn to our witness panel today. We welcome five witnesses to 
testify about the intersection of artificial intelligence and 
copyright law.
    Our first witness is Mr. Ben Brooks, head of public policy 
at Stability AI, a company that develops a range of AI models 
that help users generate images, text, audio, and video.
    Next, we have Dana Rao, executive VP, general counsel, and 
chief trust officer at Adobe. I'd like to be chief trust 
officer in the United States.
    Senator Tillis. They don't have titles like that.
    [Laughter.]
    Chair Coons. Mr. Rao leads Adobe's legal security and 
policy organization, including Adobe's Content Authenticity 
Initiative, which promotes transparency principles around the 
use of AI.
    Next, we have Professor Matthew Sag, a professor of law in 
artificial intelligence, machine learning, and data science at 
Emory University School of Law. Professor Sag is a leading U.S. 
authority on the fair use doctrine in copyright law and its 
implications for researchers in text data mining, machine 
learning, and AI.
    Next, we will hear from Karla Ortiz, an artist, a concept 
artist, illustrator, and fine artist who has worked on a 
variety of well-known and widely enjoyed projects, including 
``Jurassic World,'' ``Black Panther,'' ``Loki,'' and she is 
most famous for designing, in my assessment at least, for 
designing Doctor Strange for Marvel's first ``Doctor Strange'' 
film. Welcome.
    Last but certainly not least, we have Jeffrey Harleston, 
general counsel and executive VP of business and legal affairs 
for Universal Music Group. Mr. Harleston is responsible for 
overseeing business transactions, contracts, litigation for all 
of Universal Music Group's worldwide operations in more than 60 
countries.
    After I swear all of you in, each of you will have 5 
minutes to make an opening statement. We will then proceed to 
questioning. Each Senator, depending on attendance, 
questioning, and time, will have a first round of 5 minutes. We 
may well have a second round in 5 minutes, and we may be the 
only two left for a third round of 5 minutes, but we will see.
    So, could all the witnesses please stand to be sworn in. 
Please raise your right hand. Do you swear or affirm that the 
testimony you are about to give before this Committee will be 
the truth, the whole truth, and nothing but the truth, so help 
you God?
    [Witnesses are sworn in.]
    Chair Coons. Thank you. Mr. Brooks, you may proceed with 
your opening statement.

 STATEMENT OF BEN BROOKS, HEAD OF PUBLIC POLICY, STABILITY AI, 
                   SAN FRANCISCO, CALIFORNIA

    Mr. Brooks. Thank you, Chair Coons and Ranking Member 
Tillis, for the opportunity to testify today. AI can help to 
unlock creativity, drive innovation, and open up new 
opportunities for creators and entrepreneurs across the United 
States. As with any groundbreaking technology, AI raises 
important questions, and we recognize the depth of concern 
among creators.
    While we don't have all the answers, we are committed to an 
open and constructive dialog, and we are actively working to 
address emerging concerns through new technology standards and 
good practices.
    At Stability AI, our goal is to unlock humanity's potential 
with AI technology. We developed a range of AI models. These 
models are essentially software programs that can help a user 
to create new content.
    Our flagship model, Stable Diffusion, can take plain 
language instructions from a user and help to produce a new 
image. We are also working on research for safe language models 
that can help to produce new passages of text or software code. 
AI is a tool that can help to accelerate the creative process.
    In our written testimony, we shared examples of how 
Broadway designers, architects, photographers, and researchers 
are using our models to boost their productivity, experiment 
with new concepts, or even study new approaches to diagnosing 
complex medical disorders. We are committed to releasing our 
models openly with appropriate safeguards.
    That means we share the underlying software as a public 
resource. Creators, entrepreneurs, and researchers can 
customize these models to develop their own AI tools, build 
their own AI businesses, and find novel applications of AI that 
best support their work. Importantly, open models are 
transparent.
    We can look under the hood to scrutinize the technology for 
safety, performance, and bias. These AI models study vast 
amounts of data to understand the subtle relationships between 
words, ideas, and visual or textual features, much like a 
person visiting an art gallery or library to learn how to draw 
or how to write.
    They learn the irreducible facts and structures that make 
up our systems of communication. And through this process, they 
develop an adaptable body of knowledge that they can then apply 
to help produce new and unseen content.
    In other words, compositions that did not appear in the 
training data and may not have appeared anywhere else. These 
models don't rely on a single work in their training data, nor 
did they store their training data. But instead, they learn by 
observing recurring patterns over billions of images and 
trillions of words of text.
    We believe that developing these models is an acceptable 
and socially beneficial use of existing content that is 
permitted by fair use and helps to promote the progress of 
science and useful arts. Fair use and a culture of open 
learning is essential to recent developments in AI. It is 
essential to help make AI useful, safe, unbiased, and it is 
doubtful that these groundbreaking technologies would be 
possible without it.
    The U.S. has established global leadership in AI thanks in 
part to an adaptable and principles-based fair use doctrine 
that balances creative rights with open innovation. We 
acknowledge emerging concerns, and these are early days, and we 
don't have all the answers, but we are actively working to 
address these concerns through safe technology, standards, and 
good practices.
    First, we have committed to voluntary opt-outs so that 
creators can choose if they don't want their online work to be 
used for AI training. We have received opt-out requests for 
over 160 million images to date, and we are incorporating these 
into upcoming training. We are hoping to develop digital opt-
out labels as well that follow the content wherever it goes on 
the internet.
    Second, we are implementing features to help users and tech 
platforms identify AI content. Images generated through our 
platform can be digitally stacked with metadata and watermarks 
to indicate if the content was generated with AI.
    These signals can help ensure that users exercise 
appropriate care when interacting with AI content and help tech 
platforms distinguish AI content before amplifying it online. 
We welcome Adobe's leadership in driving the development of 
some of these open standards.
    Third, we have developed layers of mitigations to make it 
easier to do the right thing with AI and harder to do the wrong 
thing.
    Today, we filter datasets of unsafe content. We test and 
evaluate our models before release. We apply ethical use 
licenses, disclose known risks, filter content generated 
through our computing services, and implement new techniques to 
mitigate bias. As we integrate AI into the digital economy, we 
believe the community will continue to value human-generated 
art and perhaps value it at a premium.
    Smartphones didn't destroy photography, and word processors 
didn't diminish literature, despite radically transforming the 
economics of creation. Instead, they gave rise to new demand 
for services, new markets for content, and new creators.
    We expect the same will be true of AI, and we welcome an 
ongoing dialog with the creative community about the fair 
deployment of these technologies. Thank you for the opportunity 
to testify, and we welcome your questions.
    [The prepared statement of Mr. Brooks appears as a 
submission for the record.]
    Chair Coons. Thank you, Mr. Brooks. Mr. Rao.

   STATEMENT OF DANA RAO, EXECUTIVE VICE PRESIDENT, GENERAL 
   COUNSEL, AND CHIEF TRUST OFFICER, ADOBE, INC., SAN JOSE, 
                           CALIFORNIA

    Mr. Rao. Chair Coons, Ranking Member Tillis, and Members of 
the Committee, thank you for the opportunity to testify here 
today.
    My name is Dana Rao, and I am general counsel, and, as 
Senator Coons noted, chief trust officer at Adobe. I am happy 
to provide you with this secret certificate you need to get 
that title, if you would like, after the hearing.
    Since our founding in 1982, Adobe has pioneered 
transformative technologies in all types of digital creation, 
from digital documents like PDF to image editing with 
Photoshop. Our products allow our customers who range from 
aspiring artists to wartime photojournalists, to advertisers 
and more, to unleash their creativity, protect their craft, 
empower their businesses in a digital world.
    AI is the latest disruptive technology we have been 
incorporating into our tools help creators realize their 
potential. You have all seen the magic of text to image 
generative AI. Type in the prompt, cat driving a 1950s 
sportscar through the desert, and in seconds you will see 
multiple variations of a cat on a retro road trip appear before 
your eyes.
    We have launched generative AI in our own tools, Adobe 
Firefly, and has provided--this proved to be wildly popular 
with our creative professionals and consumers alike. In my 
written testimony, I explore a comprehensive framework for 
responsible AI development that includes addressing 
misinformation, harmful bias, creative rights, and intellectual 
property.
    Today, given Adobe's focus and our millions of creative 
customers and our leadership in AI, I will focus on how the 
United States can continue to lead the world in AI development 
by both supporting the access to data that AI requires and 
strengthening creator rights.
    The question of data access is critical for the development 
of AI because AI is only as powerful and as good as the data on 
which it is trained. Like the human brain, AI learns from the 
information you give it.
    In the AI's case, the data it is trained on. Training on a 
larger dataset can help ensure your results are more accurate 
because the AI has more facts to learn from. A larger dataset 
will also help the AI avoid perpetuating harmful biases in its 
results by giving it a wider breadth of experiences from which 
it can build its understanding of the world. More data means 
better answers and fewer biases.
    Given those technical realities, United States and 
governments should support access to data to ensure that AI 
innovation can flourish accurately and responsibly. However, 
one of the most important implications of AI's need for data is 
the impact on copyright and creators' rights.
    There are many outstanding questions in this space, 
including whether creating an AI model, which is a software 
program, from a set of images, is a permitted fair use. And 
whether that analysis changes if the output of that AI model 
creates an image that is substantially similar to an image on 
which it is trained.
    These questions will certainly be addressed by courts and 
perhaps Congress, and we are prepared to help assist in those 
discussions. Adobe recognized the potential impact of AI on 
creators and society, and we have taken several steps.
    First, we trained our own generative AI tool, Adobe 
Firefly, only on licensed images from our Adobe Stock 
Collection, which is a stock photography collection, openly 
licensed content, and works that are in the public domain where 
the copyright has expired. This approach supports creators and 
customers by training on a dataset that is designed to be 
commercially safe.
    In addition, we are advocating for other steps we can all 
take to strengthen creators' rights. First, we believe creators 
should be able to attach a ``Do Not Train'' tag to their work. 
With industry and Government support, we can ensure AI data 
crawlers will read and respect this tag, giving creators the 
option to keep their data out of AI training datasets.
    Second, creators using AI tools want to ensure they can 
obtain copyright protection over their work in this new era of 
AI-assisted digital creation. An AI output alone may not 
receive copyright protection, but we believe the combination of 
human expression and AI expression will and should.
    Content editing tools should enable creators to obtain a 
copyright by allowing them to distinguish the AI work from the 
human work. In my written testimony, I discuss our open 
standards-based technology content credentials, which can help 
enable both of these creator protections.
    Finally, even though Adobe has trained its AI on permitted 
work, we understand the concern that an artist can be 
economically dispossessed by an AI trained on their work that 
generates arts in their style, in the Frank Sinatra example you 
gave.
    We believe artists should be protected against this type of 
economic harm, and we propose Congress establish a new Federal 
anti-impersonation right that would give artists a right to 
enforce against someone intentionally attempting to impersonate 
their style or likeness.
    Holding people accountable who misuse AI tools is a 
solution we believe goes to the heart of some of the issues our 
customers have, and this new right would help address that 
concern. The United States has led the world through 
technological transformations in the past, and we have all 
learned it is important to be proactively responsible to the 
impact of these technologies.
    Pairing innovation with responsible innovation will ensure 
that AI ultimately becomes a transformative and true benefit to 
our society. Thank you, Chair Coons, Ranking Member Tillis, and 
Members of the Committee.
    [The prepared statement of Mr. Rao appears as a submission 
for the record.]
    Chair Coons. Thank you, Mr. Rao. Professor.

    STATEMENT OF MATTHEW SAG, PROFESSOR OF LAW, ARTIFICIAL 
    INTELLIGENCE, MACHINE LEARNING, AND DATA SCIENCE, EMORY 
           UNIVERSITY SCHOOL OF LAW, ATLANTA, GEORGIA

    Professor Sag. Chair Coons, Ranking Member Tillis, Members 
of the Subcommittee, thank you for the opportunity to testify 
here today. I am a professor of law in AI, machine learning, 
and data science at Emory University, where I was hired as part 
of Emory's AI Humanity Initiative.
    Although we are still a long way from the science fiction 
version of artificial general intelligence that thinks, feels, 
and refuses to open the pod bay doors, recent advances in 
machine learning and artificial intelligence have captured the 
public's attention and apparently lawmakers' interest.
    We now have large language models, or LLMs, that can pass 
the bar exam, carry on a conversation, create new music and new 
visual art. Nonetheless, copyright law does not and should not 
recognize computer systems as authors. Even where an AI 
produces images, text, or music that is indistinguishable from 
human authored works, it makes no sense to think of a machine 
learning program as the author.
    The Copyright Act rightly reserves copyrights for original 
works of authorship. As the Supreme Court explained long ago in 
the 1884 case of Burrow-Giles Lithographic, authorship entails 
original, intellectual conception. An AI can't produce a work 
that reflects its own original intellectual conception because 
it has none.
    Thus, when AI models produce content with little or no 
human oversight, there is no copyright in those outputs. 
However, humans using AI as tools of expression may claim 
authorship if the final form of the work reflects their 
original intellectual conception in sufficient detail. And I 
have elaborated in my written submissions how this will depend 
on the circumstances.
    Training generative AI on copyrighted works is usually fair 
use because it falls into the category of non-expressive use. 
Courts addressing technologies such as reverse engineering, 
search engines, and plagiarism detection software have held 
that these non-expressive uses are fair use. These cases 
reflect copyright's fundamental distinction between protectable 
original expression and unprotect-able facts, ideas, and 
abstractions.
    Whether training an LLM is in non-expressive use depends 
ultimately on the outputs of the model. If an LLM is trained 
properly and operated with appropriate safeguards, its outputs 
will not resemble its inputs in a way that would trigger a 
copyright liability. Training such an LLM on copyrighted works 
would thus be justified under current fair use principles.
    It is important to understand that generative AI are not 
designed to copy original expression. One of the most common 
misconceptions about generative AI is the notion that the 
training data is somehow copied into the model. Machine 
learning models are influenced by the data. They would be 
pretty useless without it. But they typically don't copy the 
data in any literal sense.
    So rather than thinking of an LLM as copying the training 
data like a scribe in a monastery, it makes more sense to think 
of it as learning from the training data like a student. If an 
LLM like GPT3 is working as intended, it doesn't copy the 
training data at all. The only copying that takes place is when 
the training corpus is assembled and pre-processed, and that is 
what you need a fair use justification for. Whether a 
generative AI produces truly new content or simply conjures up 
an infringing cut and paste of works in the training data 
depends on how it is trained.
    Accordingly, companies should adopt best practices to 
reduce the risk of copyright infringement and other related 
harms, and I have elaborated on some of these best practices in 
my written submission. Failure to adopt best practices may 
potentially undermine claims of fair use.
    Generative AI does not, in my opinion, require a major 
overhaul of the U.S. copyright system at this time.
    If Congress is considering new legislation in relation to 
AI and copyright, that legislation should be targeted at 
clarifying the application of existing fair use jurisprudence, 
not overhauling it.
    Israel, Singapore, and South Korea have recently 
incorporated fair use into their copyright statutes because 
these countries recognize that the flexibility of the fair use 
doctrine gives U.S. companies and U.S. researchers a 
significant competitive advantage.
    Several other jurisdictions, most notably Japan, the United 
Kingdom, and the European Union, have specifically adopted 
exemptions for text data mining that allow use of copyrighted 
works as training for machine learning and other purposes.
    Copyright law should encourage the developers of generative 
AI to act responsibly. However, if our laws become overly 
restrictive, then corporations and researchers will simply move 
key aspects of technology development overseas to our 
competitors.
    Thank you very much.
    [The prepared statement of Professor Sag appears as a 
submission for the record.]
    Chair Coons. Thank you, Professor. Ms. Ortiz.

      STATEMENT OF KARLA ORTIZ, CONCEPT ARTIST, ILLUSTRA-
        TOR, AND FINE ARTIST, SAN FRANCISCO, CALIFORNIA

    Ms. Ortiz. Yes. Chairman Coons, Ranking Member Tillis, and 
esteemed Members of the Committee, it is an honor to testify 
before you today about AI and copyright. My name is Karla 
Ortiz. I am a concept artist, illustrator, and fine artist, and 
you may not know my name, but you know my work.
    My paintings have shaped the worlds of blockbuster Marvel 
films and TV shows, including ``Guardians of the Galaxy 3,'' 
``Black Panther,'' ``Loki,'' you know, but specifically, the 
one I am most happiest of is that I, my work helped shape the 
look of Doctor Strange in the first ``Doctor Strange'' movie.
    I have to brag about that a little bit, sir. I love what I 
do. I love my craft. Artists train their entire lives to be 
able to bring the imaginary to life. All of us who engage in 
this craft love every little bit of it. Through hard work, 
support of loved ones, and dedication, I have been able to make 
a good living from my craft via the entertainment industry, an 
industry that thrives when artists' rights to consent, credit, 
and compensation are respected.
    I have never worried about my future as an artist until 
now. Generative AI is unlike any other technology that has come 
before. It is a technology that uniquely consumes and exploits 
the hard work, creativity, and innovation of others. No other 
tool is like this. What I found, when first researching AI, 
horrified me.
    I found that almost the entirety of my work, the work of 
almost every artist I know, and the work of hundreds of 
thousands of artists had been taken without our consent, 
credit, or compensation. These works were stolen and used to 
train for profit technologies with datasets that contain 
billions of image and text data pairs.
    Through my research, I learned many AI companies gather 
copyrighted training data by relying on a practice called data 
laundering. This is where a company outsources its data 
collection to a third party under the pretext of research to 
then immediately use commercially. I found these companies use 
big terms like ``publicly available data'' or ``openly licensed 
content'' to disguise their extensive reliance on copyrighted 
works.
    No matter what they are saying, these models are illegally 
trained on copyrighted works. To add even more insult to 
injury, I found that these for-profit companies were not only 
permitting users to use our full names to generate imagery but 
encouraging it. For example, Polish artist Frederic Koski had 
had his name used as a prompt in AI products over 400,000 
times, and those are the lower end of the estimate.
    My own name, Karla Ortiz, has also been used by these 
companies thousands of times. Never once did I give consent. 
Never once have I gotten credit. Never once have I gotten 
compensation. It should come as no surprise that major 
productions are replacing artists with generative AI.
    Goldman Sachs estimates that generative AI will diminish or 
outright destroy approximately 300 million full-time jobs 
worldwide. As Ranking Member Tillis mentioned earlier, 
copyright-reliant industries alone contribute $1.8 trillion 
value to the U.S. GDP, accounting for 7.76 percent of the 
entire U.S. economy. This is an industry that employs 9.6 
million American workers alone.
    The game plan is simple, to go as fast as possible, to 
create mesmerizing tales of progress, and to normalize the 
exploitation of artists as quickly as possible. They hope when 
we catch our breath, it will be too late to right the wrongs, 
and exploiting Americans will become an accepted way of doing 
things.
    But that game can't succeed as we are here now, giving this 
the urgency it so desperately deserves. Congress should act to 
ensure what we call the 3Cs and a T: consent, credit, 
compensation, and transparency.
    The work of artists like myself were taken without our 
consent, credit, nor compensation, and then used to compete 
with us directly in our own markets--an outrageous act that 
under any other context would immediately be seen as unfair, 
immoral, and illegal.
    Senators, there is a fundamental fairness issue here. I am 
asking Congress to address this by enacting laws that require 
these companies to obtain consent, give credit, pay 
compensation, and be transparent. Thank you.
    [The prepared statement of Ms. Ortiz appears as a 
submission for the record.]
    Chair Coons. Thank you, Ms. Ortiz. Last but certainly not 
least, Mr. Harleston.

 STATEMENT OF JEFFREY HARLESTON, GENERAL COUNSEL AND EXECUTIVE 
  VICE PRESIDENT, BUSINESS AND LEGAL AFFAIRS, UNIVERSAL MUSIC 
                GROUP, SANTA MONICA, CALIFORNIA

    Mr. Harleston. Thank you, Chairman Coons, Ranking Member 
Tillis, and Members of the Committee. It is an honor to be here 
before you today. I am Jeff Harleston. I am the general counsel 
of Universal Music Group. And what is Universal Music Group? We 
are the world leader in music-based entertainment.
    We are home to legendary record labels such as Motown, Def 
Jam, Island, Blue Note, Capitol, just to name a few. We have a 
music publishing company that signs songwriters, and we have a 
music merchandizing company as well, and an audio division--an 
audiovisual division that produces award-winning documentaries 
based on music.
    UMG identifies, develops artists across every musical 
genre. I think it is fair to note that Frank Sinatra is one of 
our artists, and I think based on what we didn't hear today, I 
am not sure if we will be pursuing a developing artist out of 
Delaware named Chris Coons, but maybe we will get back to that.
    Chair Coons. I am confident you will not.
    [Laughter.]
    Mr. Harleston. All jokes aside, I have been at the company, 
I have been honored to be with the company for 30 years, and 
most of the time I have spent as a lawyer, but I have also 
spent some time leading the Def Jam label and also as the 
management team of Geffen Records.
    So, I have been on both sides of the business. We have also 
helped broker deals with digital services, platforms, social 
media outlets where you, all of you can access the music that 
you love. It has been my life's honor to work with countless 
talented and creative artists.
    Their creativity is the soundtrack to our lives, and 
without the fundamentals of copyright, we might not have ever 
known them. I would like to make four key points to you today.
    The first, copyright artists and human creativity must be 
protected. Art and human creativity are central to our 
identity. Artists and creators have rights. They must be 
respected. If I leave you with one message today, it is this: 
AI in the service of artists and creativity can be a very, very 
good thing. But AI that uses, or worse yet, appropriates the 
work of these artists and creators and their creative 
expression, their name, their image, their likeness, their 
voice, without authorization, without consent, simply is not a 
good thing.
    The second point I want to make is that generative AI 
raises challenging issues in the copyright space. I think you 
have heard from the other panelists and they all would agree. 
We are the stewards at Universal of tens of thousands, if not 
hundreds of thousands, of copyrighted creative works from our 
songwriters and artists, and they have entrusted us to honor, 
value, and protect them.
    Today they are being used to train generative AI systems 
without authorization. This irresponsible AI is violative of 
copyright law and completely unnecessary. There is a robust 
digital marketplace today in which thousands of responsible 
companies properly obtain the rights they need to operate.
    There is no reason that the same rules that apply to 
everyone else should not apply equally to AI companies and AI 
developers.
    My third point, AI can be used responsibly to enhance 
artistic expression. Just like other technologies before, 
artists can use AI to enhance their art. AI tools have long 
been used in recording studios for drum tracks, chord 
progressions, and even creating immersive audio technologies. 
One of our distributed artists used a generative AI tool to 
simultaneously release a single in six languages in his own 
voice, on the same day. The generative AI tool extended the 
artist's creative intent and expression with his consent to new 
markets and fans instantly.
    In this case, consent is the key. There is no reason we 
can't legitimate--we can't create a legitimate AI marketplace 
in the service of artists. There is a robust free market for 
music sampling, synchronization licensing, and deals with new 
entrants to the digital marketplace, social media companies, 
and all manner of new technologies. We can do the same thing 
with AI.
    And my fourth and final point, to cultivate a lawful, 
responsible AI marketplace, Congress needs to establish rules 
that ensure creators are respected and protected.
    One way to do that is to enact a Federal right of 
publicity. Deepfakes and/or unauthorized recordings or visuals 
of artists generated by AI can lead to consumer confusion, 
unfair competition against the artist that actually was the 
original creator, market dilution, and damage to the artist's 
reputation, potentially irreparably harming their career. An 
artist's voice is often the most valuable part of their 
livelihood and public persona, and to steal it, no matter the 
means, is wrong.
    A Federal right of publicity would clarify and harmonize 
the protections currently provided at the State level. 
Visibility into AI training data is also needed. If the data on 
AI training is not transparent, then the potential for a 
healthy marketplace will be stymied as information on 
infringing content would be largely inaccessible to the 
individual creators.
    And I might add, based on some of the comments I heard 
earlier, it would be hard to opt out if you don't know what has 
been opted in.
    Finally, AI-generated content should be labeled as such. We 
are committed to protecting our artists and the authenticity of 
their creative works.
    As you all know, consumers deserve to know exactly what 
they are getting. I look forward to the discussion this 
afternoon, and I thank you for the opportunity to present my 
point of view. Thank you.
    [The prepared statement of Mr. Harleston appears as a 
submission for the record.]
    Chair Coons. Thank you, Mr. Harleston. Thank you to all of 
the witnesses today. We will begin our first 5-minute round. 
And I am going to start by just exploring how we can respect 
existing copyrighted works, copyright protections, while 
continuing to safely develop and advance AI technologies. If we 
run out of time, we will do a second round. My hunch is there 
is at least that much interest.
    Mr. Brooks, if I might just start with you. Generative AI 
models like those your company creates are trained in no small 
part on vast quantities of copyrighted content, on data from 
copyrighted content.
    Do copyright owners know if their works have been used to 
train Stability's models? Is Stability paying rights holders 
for that use? Why not, if not? And how would doing so impact 
your business and your business model?
    Mr. Brooks. Thank you, Senator. So, to the first question, 
models like Stable Diffusion are trained on open datasets or 
curated subsets of those datasets. So Stable Diffusion, for 
example, takes a 5 billion image dataset.
    We filter that for content, bias, quality, and then we use 
a 2 billion image subset to train a model like Stable 
Diffusion. Because it is open, you can go to a website, you can 
type in the URL of an image, you can type in a name.
    You can see if that work has appeared in the training 
dataset. And then we are working with partners to take those 
opt-out requests, and as I say, to incorporate them into our 
own training and development processes.
    So, we do think open datasets are important. They are one 
part of how we are able to inspect AI for fairness and bias and 
safety. And so that is I think to the first part.
    Chair Coons. So, if I heard you right, if an artist takes 
the initiative to search your training set, they might be able 
to identify that a copyrighted work was used and then submit an 
opt-out request. And you are in the process of facilitating 
that use. But to my second question, do you pay any of the 
rights holders?
    Mr. Brooks. As I say, Senator, we--this is 2 billion 
images, a large amount of content. A lot of it, you know, all 
kinds of content. Tech language models, for example, it is not 
just books, it is snippets of text from all over the internet.
    As I say, to make that workable, we believe, you know, that 
it is important to have that diversity, to have that scale. 
That is how we make these models safe. It is how we make them 
effective.
    And so--and so we collected, as I say, from online data. 
What I will say is that the datasets that we use, like that 5 
billion image dataset I mentioned, they respect protocols like 
robots.txt. So, robots.txt is a digital standard that basically 
says, I want my website to be available for ancillary purposes, 
such as search engine indexing.
    And so, the dataset that was compiled respected that 
robots.txt signal, and then on top of that, as I say, we have 
the opt-out facility that we have implemented.
    Chair Coons. Thank you. Mr. Rao, it is my understanding 
that Adobe is taking a distinctly different approach. Your 
generative AI model, Firefly, was only trained on licensed 
data. Were there any downsides economically to that decision? 
Is your model less robust or has it had any impact on its 
performance? And how would you compare these two approaches in 
terms of the incorporation of opt-out and licensed?
    Mr. Rao. Thank you for the question. So, as I mentioned in 
the opening remarks, that we--Firefly, our generative AI tool 
was trained on our stock photography collection, which are all 
licensed assets with the contributors, and that is actually the 
only dataset used in the version that you can use on Firefly on 
the web.
    We think about the quality of this, and when we think about 
the quality to your question, we have to put a lot of image 
science behind that to make sure it was up to the level we 
require because we didn't have the most expensive version of 
that dataset. So, we had to put more computer science behind it 
to make it have the higher quality we needed.
    As we go forward, we are looking at whether or not there 
are other areas where we need to supplement that dataset, and 
for those we referred to as opening licensed content or places 
where the copyright has expired.
    Opening licensed to us means images that come from the 
rights holders who have licensed it without restriction. So, 
very similar to what we are talking about in the licensed 
content, this is a place--this is also what we call 
commercially safe.
    Chair Coons. My sense, Mr. Brooks, is Stability is trying 
to honor something like 160 million opt-out requests in 
training your next model. Mr. Rao, Mr. Brooks, just this will 
be my last question, and then I will turn to Senator Tillis. 
Should Congress be working to ensure that creatives can opt out 
of having their works used to train AI models? How would you 
best do that, briefly?
    Mr. Rao. So, we have this technology we refer to as content 
credentials in my opening remarks, and what that does, it is a 
metadata that goes along with any content. So, if you are in 
Photoshop right now, you can say, I want content credentials to 
be associated with this image.
    As part of that, you can choose to say, I want it not to be 
trained on it--a ``Do Not Train'' tag that gets associated with 
the image and it goes wherever the content goes.
    So, we do think the technology is there and available, and 
we are talking to other companies, including Stability, about 
this as an approach to honor that tag so people who are 
crawling it can see the tag and choose not to train on them.
    Chair Coons. Should we require that?
    Mr. Rao. And I do think that there is an opportunity for 
Congress to mandate the carrying of a tag like that, a 
credential like that, wherever the content goes. Right now, it 
is a voluntary decision to choose to do that.
    Chair Coons. Should we require that?
    Mr. Brooks. There is some very interesting precedent 
internationally for this. The European Union has introduced 
certain kinds of text and data mining exceptions. And part of 
that is to say that you can use this for commercial, 
noncommercial purposes.
    There is an opt-out requirement, but the opt-out has to be 
machine readable, as I say, as a matter of practicality, when 
you are dealing with trillions of words of content, for 
example, or billions of images, in this case.
    The machine readability is important, and that is where 
these tags become an important part of how to implement it in 
practice.
    Chair Coons. We will keep exploring this further. Senator 
Tillis.
    Senator Tillis. Thank you, Chairman. I'll have Senator 
Blackburn go and then I will follow Senator Hirono.
    Senator Blackburn. Excellent. Thank you, Senator Tillis. 
And Mr. Chairman, thank you for the hearing today. It is so 
appropriate that we have this. I am from Tennessee. We have 
thousands of artists and songwriters and musicians, and we have 
actors and actresses, and we have authors and publishers.
    And everywhere I go, people are talking about the impact of 
AI, to the positive or the negative. You know, you look at 
health care, you look at logistics, you look at autos, you look 
at entertainment, and there are pros and cons.
    But the one point of agreement is, we've got to do 
something about this so that it is going to be fair, and it is 
going to be level. Mr. Harleston, I want to come to you right 
off the bat because you mentioned the NIL issue, which I think 
is an imperative for artists to be able to own that.
    And you also mentioned the right of publicity laws, and of 
course, those are State level laws. And as you rightly said, we 
don't have a federally preemptive right to publicity law. And I 
think the dust up--a lot of people came to realize this over 
Drake and The Weeknd, and ``heart on my sleeve.''
    And this is something that does have to be addressed. So, 
for the record, give us about 30 seconds and then you guys, I 
see your capable team behind you, you can submit something 
longer in writing, if you would like, on the reason State level 
publicity laws are not enough.
    Mr. Harleston. In 30 seconds----
    [Laughter.]
    Mr. Harleston. State level publicity laws are inconsistent 
from State to State. A Federal right of publicity that really 
elevates right of publicity to an intellectual property is 
critically important to protect----
    Senator Blackburn. Okay, I am going to help you out with 
this----
    Mr. Harleston. Okay.
    Senator Blackburn. A federally preemptive right to 
publicity law would provide more of that constitutional 
guarantee to her works that Ms. Ortiz has mentioned.
    Mr. Harleston. Absolutely.
    Senator Blackburn. All right. And----
    Mr. Harleston. And we will follow up with you, Senator.
    Senator Blackburn. Yes, excellent. I think something in 
writing would be very helpful there. Now, I think it was very 
appropriate that you had Spotify and Apple Music take down 
``heart on my sleeve.'' Important to do. And talk about the 
role that the streaming platforms should play. Should they be 
the arbiter when it comes to dealing with this generative AI 
content?
    Mr. Harleston. These streaming platforms, we acknowledge 
that they are in a challenging position, but certainly in some 
instances when there is clear, or it is clear that the content 
that has been submitted to them for distribution----
    Senator Blackburn. So, a knowing and willingness standard 
would be nice.
    Mr. Harleston. That would be very nice, yes.
    Senator Blackburn. Okay. I am helping you out there.
    Mr. Harleston. You are doing great.
    Senator Blackburn. Thanks for being here.
    Okay, Professor Sag, want to come to you. This spring, the 
Supreme Court issued a--what I thought was a very appropriate 
decision in Warhol v. Goldsmith, and I was very pleased to see 
them come down on the side of the artist. I filed an amicus 
brief in this case arguing for strong, fair use protections for 
creators. Now, we have been through this thing in the music 
industry where ``fair use'' became a fairly useful way to steal 
my property.
    And artists don't want to go through that again. Right, Ms. 
Ortiz?
    [Voice off microphone.]
    Senator Blackburn. It didn't work the way it was supposed 
to. And I would like for you to talk for a moment, should AI, 
unlicensed AI ingestion of copyrighted works might be 
considered fair use when the output of AI replaces or competes 
with the human-generated work.
    Now, Ms. Ortiz has laid this out fairly well in her 
comments and the Supreme Court has sided with the artist in 
Warhol v. Goldsmith. But this fair use standard comes into play 
every time we talk about our fabulous creative community and 
keeping them compensated. So, the floor is yours.
    Professor Sag. Senator Blackburn, commercial replacement 
should not be the test. The test should be exactly what the 
Supreme Court said in the Andy Warhol case.
    The question is, is this significantly transformative? What 
that means in relation to training AI models is, does the 
output of the model bear too much resemblance to the inputs? 
And that is a different question to, is it competing with the 
inputs? Could it be used as a commercial substitute?
    If you look at some of the old cases on reverse engineering 
software, companies were allowed to crack open software, find 
the secret keys to interoperability, and build new competing 
products that did not contain any copyrightable expression, and 
the Court said that that was fair use.
    So, I think on current law, the answer is no. Potential 
substitution in terms of a competing product is not the test. 
The test is, are you taking an inappropriate amount of an 
artist's original expression.
    Senator Blackburn. Well, my time has expired. Thank you for 
that. We just don't want it to become a fairly useful way to 
steal an artist's product. Thank you, Mr. Chairman.
    Chair Coons. Thank you, Senator Blackburn. And thank you 
for the passionate engagement you have always brought to these 
issues on behalf of the creative community.
    [Laughter.]
    Chair Coons. Senator Hirono.
    Senator Hirono. Thank you, Mr. Chairman. Mr. Harleston, 
whenever the idea of negotiating licenses is raised, people 
express concerns about how complex it would be and how AI 
platform developers could never possibly negotiate with all 
rights holders. But in the music context, at least, you have a 
lot of experience negotiating rights.
    Could you tell us a little bit about your industry's 
history of negotiating rights with digital music services and 
lessons that history could teach us, for whether rights 
negotiations would be possible with AI platforms?
    Mr. Harleston. Thank you, Senator. As you referenced, we 
have had a long history with the transition of our business 
from a physical business to a digital business, and having to 
encounter digital platforms that were very quickly adapted by 
consumers and had lots of our content on there.
    What we found was ingenuity does play a role. It is not 
easy. But we were able to identify or find ways to identify our 
copyrights, to work out licensing schemes that allowed the 
platforms to be able to carry and distribute the music.
    And in a commercial environment that was positive for them, 
while at the same time allowing the artists to be properly 
compensated. And this is, you know, with the--in the music 
side, we have two sets of rights, which makes it even more 
complicated, but we have done great work over the years to 
develop systems that allow identifying not only the sound 
recording, but also the underlying composition.
    So, it could be done. But what it needs, it needs--what we 
would need is we need help to make sure that everyone 
understands that there are rights that are affected and that 
the activity that is happening now is violative. And once they 
understand that what they are doing is violative, that brings 
them to the table so we can negotiate a deal.
    Senator Hirono. I note that in your testimony you said that 
consent is the key. So is your position that every artist's 
work before it can be used to train AI models, that the company 
that is wanting to use that information has got to get the 
consent of the originator?
    Mr. Harleston. In a very short answer, yes.
    Senator Hirono. And you think that we are able to do this 
knowing that these platforms incorporate billions and billions 
of information to train their AI models?
    Mr. Harleston. Understanding that, but it absolutely could 
be done as these--as the digital platforms that exist today, 
the licensed platforms ingest millions and millions of songs 
every week. So, it is not a problem in that respect. There is 
metadata that we could license. We could absolutely do that. 
But there has to be an initiative on the side of the companies 
to reach out.
    Senator Hirono. So, Ms. Ortiz, if I--Mr. Brooks, rather, 
sorry. My--what I heard you say in response to the Chairman's 
question is that for all of the data that you input into your 
model, you do not get the consent of the artist or originator. 
Is that correct, Mr. Brooks?
    Mr. Brooks. So, we, Senator, we believe that yes, if that 
image data is on the internet and robots.txt says it can be 
subject to aggregated data collection, and if it is not subject 
to an opt-out request in our upcoming models, then certainly we 
will use those images, potentially use those images if it 
passes our filters.
    Senator Hirono. So basically, you don't pay for the data 
that you put into your--to train your model.
    Mr. Brooks. For the base, the kind of initial training or 
teaching of these models with those billions of images, there 
is no arrangement in place.
    Senator Hirono. So, you have Ms. Ortiz who says that that 
is wrong. Is that correct, Ms. Ortiz?
    Ms. Ortiz. One hundred percent, Senator.
    Senator Hirono. So do you know if--well, I think you 
mentioned that your work has been used to train AI models and 
you have gotten not one cent for that use.
    Ms. Ortiz. I have never been asked. I have never been 
credited. I have never been compensated one penny. And that is 
for the use of almost the entirety of my work, both personal 
and commercial, Senator.
    Senator Hirono. So, if you were to allow your works to be 
used to train, you would--do you think that you would 
negotiate--if there was a law that required compensation, then 
that compensation negotiation should be left to you and the 
entity such as Mr. Brooks'.
    Ms. Ortiz. Personally, I love what I do, so I wouldn't 
outsource it to an AI, but that is not a choice for me to make, 
and it is all about that. It is about being able to have that 
choice and artists don't have that right now.
    Senator Hirono. Thank you.
    Senator Tillis. Thank you, Mr. Chair. I was actually 
inspired by one of the opening statements, so I went out and 
generated a cat driving a 1960 Corvette with a surfboard in it. 
And I produced that picture.
    [Phone is held up with the screen facing the witnesses.]
    Senator Tillis. Actually, it gave me four options. This one 
I found the most interesting. But it raised a question that I 
wanted to ask you, Mr. Brooks. If an artist looked at that and 
said, that is in part developed by that 60s Corvette in South 
Beach, how does that artist then go about saying--I am trying 
to get an understanding of your current opt-out policy.
    And one of the issues that we have had here and not 
completely related, but we have a notice, a takedown notice and 
stay down discussion in the past around creative works. So, I 
was just trying to understand, and I think it is going to be a 
lengthy answer. And then if I talk to a creative, it is going 
to be a lengthy answer.
    But for the record, it would be very helpful to me for your 
specific platform to understand how that opt-out process works. 
I think I heard right that you could embed within the works 
certain things that already create an opt-out, or that that 
work shouldn't be used. But I want to drill down. We don't have 
time to do that now.
    And in a twist of irony, I was wondering if any of the 
witnesses would suggest any creative works by other 
governmental bodies that we should steal and use as a baseline. 
In other words, what good policy seems to be being discussed or 
passed? What particularly problematic at either end of the 
spectrum? Because I am sympathetic to the issues at both ends 
of the spectrum on this argument.
    So maybe we start with you, Professor. Are you aware of any 
Western democracy states, I am not particularly interested in 
what China is doing because whatever they agree to, they are 
going to rip off anyway, but any best practices that we should 
look out there, or bad practices, or trends that we should 
avoid or be concerned with as we move forward?
    Professor Sag. I think that the European Union's approach, 
where they have different rules for commercial and 
noncommercial use, and opt-outs have to be respected for 
commercial uses of the text mining in Article 4 of the DSM has 
something to recommend it.
    By the same token, I would note that opt-outs do not apply 
to researchers working at proper research institutions in the 
EU, nor do contractual overrides, which is a position that I 
can't see Congress adopting, but it is certainly something to 
look at. That's--that's really it.
    Senator Tillis. Anyone else briefly could add what--Ms. 
Ortiz, I should also add, I have seen all your works and it has 
been since 11 o'clock last night that I was talking about 
``Guardians of the Galaxy'' with my colleagues as we were 
coming back from Vilnius.
    Ms. Ortiz. It was a really fun project to work on, Senator, 
so thank you. So, what the artists community have suggested is 
that models be built starting from scratch via public domain-
only works, that's work that belongs to everyone. Any expansion 
upon that to be done via licensing. And there is a couple of 
reasons for this.
    Current opt-out measures are inefficient. For starters, 
machine learning models, once they are trained on data, they 
cannot forget. And machine unlearning procedures are just dead 
on the water right now, and this is not according to me. I am 
an artist. I have no idea on this. This is according to machine 
learning experts in the field.
    Second, things, safety filters like, for example, prompt, 
you know, filters are so easily bypassed by users. So 
unfortunately, when companies say, hey, opt out, there is no 
real way to do that. But even further, what happens if someone 
doesn't know how to write a robot.txt?
    Like, how does a person who may not know the language, may 
not know the internet, may not even know that their work is in 
there, recognize that, you know, they need to opt out. This is 
why my community in particular has suggested over and over, opt 
in should be the key in order to base the foundations of 
consent, credit, and compensation.
    Senator Tillis. And Mr. Brooks, I can understand the 
challenges with opt-in versus opt-out in terms of the task that 
you would have ahead of you. But what is your view of the 
concerns that creatives have expressed in this light and the 
current opt-out process that you all have in place or 
procedures which I would like to get information for, for the 
record.
    Mr. Brooks. Thank you, Ranking Member. Look, I will say at 
the start that we do need to think through what the future of 
the digital economy looks like. What do incentives look like? 
How do we make these technologies a win-win for everyone 
involved? These are very early days from our perspective. We 
don't have all the answers, but we are working to think through 
what that looks like----
    Senator Tillis. I am going to stick around for a second 
round, so we will get a little bit deeper into that. But I want 
to defer to my colleague from California.
    Chair Coons. Thank you, Senator Tillis. Senator Padilla.
    Senator Padilla. Thank you, Mr. Chair. And I want to thank 
the witnesses for your testimony and participation today. 
Speaking of California, I can't help but observe that 
California is very well represented on this panel. Not only a 
point of pride for me as a Senator from California, but it is 
frankly not a surprise since we are the creative and tech hub 
of the Nation.
    Now, generative AI tools, as we have been talking about, 
present remarkable opportunities and challenges for the 
creative community and our broader society. And I couldn't help 
but observe that in reviewing the testimony from each of you, I 
noted the common goal of seeking to leverage and develop AI 
tools to complement and encourage human creativity and 
artistry, while also respecting the rights and dignity of the 
original creators.
    So, it is a tall order, a delicate balancing act in many 
ways, but that is--this seems to be the shared objective here. 
So, I want to thank you again for participating in this hearing 
as we are working to determine what role we play in fostering 
the development of AI in a manner that is a net positive for 
innovation and creativity.
    My first question, and I will keep it brief because it is 
sort of piggybacking on--Senator Hirono has raised it, Senator 
Tillis was just trying to expand upon it, and is directed at 
Mr. Brooks. This whole opt in, opt out: We can talk about what 
the process is, whether it is easy, clear, or not for artists.
    And, you know, I don't completely agree with you that we 
are in an early stage because it is happening fast. Tell me how 
it is possible--explain how it works to have a system unlearn 
inputs that have already been taken, if you get this after-the-
fact opt-out from an artist. It is happening now. While you are 
trying to think what it means long term, it is happening now.
    So how does it work, not just process, checking a box, 
filling out a form, but technically?
    Mr. Brooks. Thank you, Senator. So, just in terms of the 
data collection piece, I just want to make it clear that today 
it is very much a kind of work in process framework. You know, 
you can go to this website. You can indicate you want to opt 
out. We will take those opt-out requests as they come in.
    But as we were talking about before, it is important that 
eventually there is a standardized kind of metadata that just 
attaches to these works as they go out into the wild. And as I 
said, that is what the EU is requiring, and I think there will 
be a lot of standards development in that space, again, with--
in terms like Adobe and others.
    In terms of what then happens, you know, as I say, we 
filter that training data for a few reasons. We take out unsafe 
content, we adjust for issues like bias to correct the bias. 
And then in addition to that, we start to incorporate, as I 
say, the opt-out requests.
    Sometimes some of the models we release are retrained from 
scratch with new datasets. Again, they take into account the 
lessons learned through previous development, both as an 
organization, as a company, and potentially technical things 
that we have learned as well in that process.
    Some of the models that are released are just fine-tuned 
variations of the model, and so those ones may have the same 
kind of basic knowledge from that original training process, 
and there has just been some additional training to correct for 
certain behaviors or improve performance in specific tasks.
    So, in terms of, you know, the future of this space, you 
know, there is a lot of work being done on unlearning in 
general. You know, how do you interpret the relationship 
between training and the data in training and the performance 
of the model?
    How do you potentially adjust to that, different ways? But 
as I say, at this stage, we treat it as a process of 
incorporating those opt-out requests, retraining, and then 
releasing a new model trained on that new dataset.
    Senator Padilla. I hear you, and I just want a level set a 
little bit, not just out of the concern for the artists, but 
knowing that unless you are getting one, two, three inputs 
today, which may be small enough to keep your arms around, I 
doubt that is the case as we are getting into the hundreds and 
thousands of inputs per day to go in and relearn, unlearn, and 
comply with any consent or opt-out. It gets overwhelming and 
unfeasible real quick, and it is happening now.
    I also wanted to follow up on a subject matter that Senator 
Coons touched on earlier. We know that generative AI models 
need to be fed large datasets to learn how to generate images 
based on user prompts, just like Senator Tillis did. By the 
way, that looked much more like Pacific Coast Highway than 
South Beach.
    Now, AI for--this is now talking to folks back home, can 
only understand what it is taught, making it critical that for 
AI companies to train their models with data that captures the 
full range of the human experience, want to be inclusive and 
diverse, if we are going to be accurate in representing our 
users, representing the diverse backgrounds of all users.
    Now, Mr. Rao, you have explained how Adobe's Firefly seeks 
to avoid copyright infringement by being trained on only 
licensed Adobe Stock images, openly licensed content, and 
public domain content.
    So how do you reconcile both? You want to be as inclusive 
as possible, which means as much data input as possible, but to 
avoid the copyright infringement, you are being selective in 
those inputs. That diversity of input is important, I think, 
for the diversity of output. So how do you reconcile?
    Mr. Rao. It is definitely a tension in the system. Right? 
The more data you have, the less bias you will see. So, it is 
great to have more data.
    But when you set the expectations that we had for ourselves 
of trying to design a model that was going to be commercially 
safe, we took on the challenge of saying, can we also do that 
and minimize harmful bias? And the way we did that, we have an 
AI ethics team. We started that 4 years ago.
    And one of the key things they did when we were developing 
Adobe Firefly was not only do we have the dataset and we 
understand what that is, we also did a lot of testing on it. We 
have a series of prompts, hundreds and hundreds and hundreds of 
prompts.
    We were testing against it to see what the distribution of 
model is. Is there going to be a bias. If you type in 
``lawyer,'' are you only going to get men--or white men, and 
what does that mean, and how, then, do you change that?
    And you either change it by adding more data, making it 
more diverse--and so that means you have to get ethically-
sourced, more data to diversify the dataset, or you can add 
filters on top of the dataset to force a distribution of what 
you expect to see if you are typing in certain search terms and 
make sure the bias is removed.
    So, you can either do it by adding more data or you can do 
it with through adding filters on top of the model itself to 
ensure that you are going to get the right result.
    Senator Padilla. And if you ask--if you input ``Senator,'' 
what comes out?
    Mr. Rao. An amazingly handsome man and woman, just very 
intellectual.
    [Laughter.]
    Senator Padilla. Men and women--colors across the spectrum.
    Mr. Rao. Across the spectrum.
    Senator Padilla. Thank you, Mr. Chair.
    Mr. Rao. The first time we did ``lawyer,'' though, we only 
had white men. And as general counsel, I was like, there should 
be some people who look like me as well.
    Chair Coons. Thank you, Senator Padilla. Senator Klobuchar.
    Senator Klobuchar. Okay, very good. Thank you. I was glad 
to be here for all your testimony and thank you for that. I 
guess, I will start with you, Mr. Harleston. Approximately, and 
I know you talked about this a bit with some of the other 
Senators, Senator Blackburn. Approximately half the States have 
laws that give individuals control over the use of their name, 
image, and voice.
    But in the other half of the country, someone who was 
harmed by a fake recording purporting to be them has little 
recourse. In your testimony, you talk about new laws and how 
they could protect musicians' names, likenesses, and voices--
the right of publicity, I think you called it.
    Can you talk about why creating this is important in the 
face of emerging AI? And how have statutes in States that have 
these protections helped artists?
    Mr. Harleston. Thank you, Senator, for the question. It is 
critical in this environment when we are talking about the 
creative expression that the artist has made, that the right of 
publicity also be extended at the Federal level.
    There is inconsistency, but more importantly, the 
preemptive element of it is critical. Raising it to the level 
of an intellectual property is also critical. What we have 
seen, and this is really in the area of deepfakes, where you 
have seen, I think, Ms. Ortiz referenced how many times her 
name was listed.
    We are finding with our artists, particularly the ones that 
are most established, that their names are, you know, daily--
hundreds and hundreds of thousands of posts with their names. 
And also, there is sometimes images that are used as well.
    Senator Klobuchar. Mm-hmm.
    Mr. Harleston. So, it is critical to have this right to 
protect the artists and their use. And if I could just say one 
thing on the--I know this is not your question, but I have to 
say----
    Senator Klobuchar. There we go.
    Mr. Harleston. Because it is killing me----
    Senator Klobuchar. I will just add it to my time.
    [Laughter.]
    Mr. Harleston. All right, thank you, thank you. On the opt 
in, opt out, there is an element beyond commerciality. And I 
want to make sure everyone understands. Ms. Ortiz did reference 
it, about she didn't really--she probably wouldn't want a 
license to AI. And there are--we have artists that don't want a 
license to streaming services. So, they are not--it is not 
always about the commerciality.
    Some artists just don't want their art distributed in 
certain ways. And the Beatles didn't come onto streaming 
platforms till about 7 or 8 years ago. That was a decision that 
was very important to them. So, I want to add that into the 
conversation. I know that wasn't your question, sorry.
    Senator Klobuchar. Okay, very good. And so, what do you see 
as the obligations of social media platforms on this?
    Mr. Harleston. With respect to AI?
    Senator Klobuchar. Uh-huh.
    Mr. Harleston. Oh, great--fantastic question. We believe 
that the social media platforms absolutely have an obligation. 
I will say this, that we could help them by giving them a hook 
beyond copyright in terms of being able to take down some of 
the----
    Senator Klobuchar. Exactly----
    Mr. Harleston. Some of the deepfakes. They have challenges 
with some of the platforms on this.
    Senator Klobuchar. Yes. Right, exactly. And I think we are 
seeing the same thing. I guess I would turn to you, Mr. Brooks. 
You talked about advocating for creating ways to help people 
identify AI-created content.
    And when we talk about deepfakes, we are already seeing 
this with political ads, and not even paid ads, just videos 
that are put out there. There's one of my colleague Senator 
Warren that was just a total lie that, saying that--acting like 
it was her that she was saying people from one party shouldn't 
be able to vote.
    And we have seen it in the Republican Presidential primary. 
A number of us on a bipartisan basis are working on this. I 
chair the Rules Committee, so it is kind of my other hat.
    Do you agree that without tools for people to determine 
whether an image or video generated by AI, that that would pose 
a risk to our free and fair elections, if you can't tell if the 
candidate you are seeing is the candidate or not?
    Mr. Brooks. Thank you, Senator. We absolutely believe that 
these transparency initiatives like CAI with Adobe are a really 
important part of how we make the information ecosystem more 
robust.
    This isn't just an AI problem or a social media problem. It 
is going to require everyone, and it is going to require 
accountability right across that ecosystem. But what we think 
is, you know, we have in place things like metadata, things 
like watermarking for content.
    They are just some more of the signals that social media 
platforms can use to decide whether they are going to amplify 
certain content.
    Senator Klobuchar. Yes, and we have got this REAL Political 
Advertisement Act, with Senator Booker and Senator Bennet. 
There is a version initially that was also introduced in the 
House. And so, that is one solution.
    But we are also going to have to look at, I would say, 
banning some of this content, because even a label or a 
watermark--it is not going to help the artist or the candidate 
if everyone thinks it is them and it is not, and then at the 
end, it says generated by AI.
    Mr. Brooks. It is a great question and a really important 
one, I think, Senator, because there are a few things in there. 
I think there's the question of the use of likeness, 
particularly for improper purposes, where you are implying that 
there is some kind of endorsement or affiliation between a 
particular person and a particular work or idea.
    That is different, I think, to the use of the kind of free 
experimentation with style and some of these other issues that 
tend to get lumped together in AI outputs.
    Senator Klobuchar. Mm-hmm.
    Mr. Brooks. And so, in terms of these scenarios that you 
are talking about, there is this kind of improper use.
    You are implying that someone endorses or embraces a cause 
or a work that they are not affiliated with. And there needs to 
be clear rules around how like this is used in that context, 
whether through right of publicity or through some of the 
bespoke deepfake legislation.
    Senator Klobuchar. Okay. Last, Mr. Rao, our recent study--
and I know you have worked on this democracy issue, which I 
truly appreciate. A recent study by Northwestern predicted that 
one third of the U.S. newspapers that existed roughly 2 decades 
ago will be gone by 2025.
    The bill that Senator Kennedy and I have, the Journalism 
Competition and Preservation Act, would allow local news 
organizations to negotiate with online platforms, including 
generative AI platforms.
    This bill passed through this Committee now twice. Could 
you describe how Adobe approaches this issue? And in your 
experience, is it possible to train sophisticated, generative 
AI models without using copyrighted materials, absent consent?
    Mr. Rao. Thanks for the question. Absolutely. We--our 
current model that is out there is trained using the licensed 
content that I had mentioned before and other content that has 
no restrictions on it, and it comes from the rights holders 
directly.
    So, we definitely think it is possible. We have done it. It 
is out there on our website, and it is also in Photoshop, and 
people love it. The creative professionals are using that AI. 
It makes their day easy.
    It lets them start their creative work in just one click 
and then they finish it in the tool. So, it has really 
revolutionized how we think about things. In terms of how we 
acquire datasets, and we have a group inside Adobe whose--that 
is their job. Their job is to think about where do we need to 
go next? Do we need to get to different media types? Do we--are 
we missing some sort of subject matter for our AI to be more 
accurate?
    That was a question we had before. We think about that 
content. Maybe there is a newspaper that you mentioned that has 
the kind of content we need. We go approach that organization 
and say, look, we need to license that content in to make sure 
our AI is more accurate.
    So, we have a team that thinks about this--sources it, and 
brings it in.
    Senator Klobuchar. And in the absence of that? I mean, what 
impacts do you anticipate this could have on local journalism 
if there are no rules of the road put in place?
    Mr. Rao. Yes, I think that, you know, both on the 
authenticity side and on this side, if people are able to, you 
know, create images and these newspapers are not able to get, 
you know, the ability to license the work they are doing, it 
could certainly have a negative impact to them.
    On the authenticity side, the reason why so many media 
companies have joined the Content Authenticity Initiative, like 
AP, Reuters, Wall Street Journal, New York Times, Washington 
Post, is because they know that when they are showing images, 
they need to be able to show that they are actually true.
    Senator Klobuchar. Mm-hmm.
    Mr. Rao. They need to be able to prove that it happened. If 
people stop believing that any of these digital images they are 
seeing are real, then they are going to stop consuming 
newspapers. They are going to stop consuming that content 
because they are not going to believe it. So, you have to give 
those local newspapers a way to prove what they are showing is 
true----
    Senator Klobuchar. Right. Absolutely.
    Mr. Rao [continuing]. So people can still consume it.
    Senator Klobuchar. Of course, there is a lot less famous 
newspapers, including some very small ones in my State that 
just you might not mention. Right?
    And so, I think that part of it, is that, you know, the Ms. 
Ortizes of this story need to be able to have some kind of 
power to be able to protect their content, too, because they 
don't have a general counsel, and they are not going to be able 
to, on their own, start some major lawsuit. And so, I think 
that is how we have to think about that, too, as we look at all 
of this.
    Mr. Rao. And that is why I would say again that when we 
designed the Firefly, we designed it that way. Right?
    Senator Klobuchar. Mm-hmm.
    Mr. Rao [continuing]. To be commercially safe first, right, 
making sure that we built the model the way----
    Senator Klobuchar. Yes, no, I am not--I am saying it sort 
of rhetorically to the world and to everyone that needs to get 
this done, as opposed to you, Mr. Rao.
    Mr. Rao. Thank you so much.
    Senator Klobuchar. All right. Appreciate it. And I thank 
you, both of you, for your continual bipartisan work in taking 
on this very important issue. Thanks.
    Chair Coons. Thank you, Senator Klobuchar. We are going to 
do a last round of questioning. We may be joined by other 
colleagues, but we are also in the middle of a vote. So, my 
hunch is we will resolve this in 10 to 15 minutes at the most, 
if I might.
    I am interested in pursuing the question of a Federal 
statutory right of publicity. And to me, the core issue really 
is, what is the remedy?
    Often, preemption is motivated by a desire for there to be 
consistency, the elevation in terms of process and access to 
justice, and potential remedies that comes with a Federal right 
as opposed to a State right.
    But, Professor, if I could start with you. You testified 
earlier in response to a question from Senator Blackburn that 
commercial replacement is not the appropriate test under 
current fair use law in the United States.
    Should we adopt a Federal right of publicity with 
commercial replacement as the test or part of the test, and how 
would that play out? What other remedy might you suggest under 
a new Federal right of publicity?
    Professor Sag. Senator, thank you for that question, 
because I was quite alarmed by some of the discourse here about 
the right of publicity. I think, as well as----
    Chair Coons. Regulated by discourse.
    Professor Sag [continuing]. As well as thinking about 
publicity rights for well-known artists, musicians, etcetera, 
Congress should be thinking about the right of publicity of 
ordinary people, people who are anonymous, people who have no 
commercially valuable reputation.
    All of us deserve to be protected from deepfakes and 
synthetic reproductions of our name, image, and likeness, 
regardless of whether we are a famous politician or a famous 
artist or just an anonymous law professor. So, I think----
    Chair Coons. How would you focus the remedy in order to 
make that effective?
    Professor Sag. Senator, in terms of remedy, I think that 
right of publicity statutes have traditionally had injunctive 
relief, usually incorporating equitable balancing tests. That 
is the remedy I would go for, which would mean, the models 
might have to be retrained.
    Chair Coons. Injunctive relief only, not commercial?
    Professor Sag. Damages, potential as well. But statutory 
damages, I don't think so. Statutory damages can be quite 
distorting. They tend to be a honeypot for opportunistic 
lawyers, as well as genuinely aggrieved plaintiffs. So, I would 
steer clear of statutory damages, but actual damage and 
injunctions, absolutely.
    Chair Coons. Mr. Rao, I'd be interested in your views on 
what a right of publicity might potentially do. I'd also be 
interested in hearing your thoughts on how we should be trying 
to balance respecting copyright through this or other means, 
while incentivizing investment in AI and accelerating 
innovation in the United States?
    Mr. Rao. Thank you for the question. So, we talked about in 
our testimony similar to, but not exactly like, a right of 
publicity.
    We referred to as a Federal anti-impersonation right. And 
the reason we thought about it from an anti-impersonation 
perspective is actually some of the same questions Professor 
Sag raised, which is we want to make sure Professor Sag himself 
is not--does not have a deepfake made of him.
    So, if you think about it as an impersonation right, that 
would apply to everybody. And what we are really targeting 
there is we see the economic displacement that we have been 
talking about here, where an AI is trained on an artist and 
creates an output that is exactly like the artist, and they are 
getting displaced by that work.
    And copyright may not reach them, like that has been the 
question. So that is why we believe they do need this right so 
they can go after these people who are impersonating work, 
whether that is likeness, whether that is style.
    And then the test would be something that we would work out 
through 6 months of deliberation here in this body, exactly how 
you would decide that. But I think that is the right approach, 
because you want to focus on people who are intentionally 
impersonating someone in order to make or get some commercial 
benefit, and I think that will help clarify what harm we are 
trying to address.
    Chair Coons. Mr. Brooks, how do you think a Federal anti-
impersonation right----
    Mr. Rao. By the way, that spells FAIR. Just want to make 
that clear. I know how Congress loves acronyms. Yes?
    Chair Coons. We are enthusiastic about acronyms. We 
actually are producing a Senate-only version of ChatGPT that 
only produces acronyms for bill names.
    [Laughter.]
    Chair Coons. Mr. Brooks, how do you think a Federal 
publicity right or an anti-impersonation right, a Federal 
requirement that there be opt-in only rather than opt-out would 
impact the business model that you are currently representing?
    Mr. Brooks. So, Chair Coons, I think the actual instrument 
and the content of that instrument, I think is really 
diagnostic at this stage. As I said to Senator Klobuchar, it is 
important from our perspective that there are clear rules 
governing the use of likeness in an improper way.
    I think the important thing to stress there is that it is a 
use. And to some extent we can't escape the fact that the 
determination of whether it is proper or improper will depend 
on the application, what the user does or does not do with that 
content downstream.
    And so, as I say, you know, from our perspective, the lines 
in the sand between improper use of likeness, free 
experimentation with style, or other kinds of good or bad use 
of these tools aren't easy to draw.
    They are very fact sensitive. It may be appropriate for 
courts to determine that. But at a high level, as I say, I 
think there is a core of things around that improper use of 
likeness, especially voice likeness, that there may be some 
legislative intervention there that makes sense and may have 
obligations, as I say, across the supply chain, across the 
ecosystem.
    Chair Coons. Mr. Harleston, if I might, the Copyright 
Office recently issued guidance about human authorship being 
critical to any copyright protection.
    Is their guidance accessible enough, relevant? Did they 
strike the right balance? Should we be looking at a different 
policy in terms of how broadly copyright protection should 
reach when there is AI assisted creativity as opposed to AI 
generated?
    Mr. Harleston. I think the Copyright Office did a pretty 
good job. One can debate whether an AI component in a broader 
work should also be afforded some form of copyright. You know, 
I think they landed in the right place, that it shouldn't. That 
copyright should only be afforded to human creation.
    So, for example, if you had an AI-generated song--well, if 
you had a song that was created by an artist and they used--a 
piece of it was generative AI, there should be a copyright in 
that entire work, but the AI-generated portion would not be 
protectable.
    So, if someone were to actually sample it, which would lift 
it out and use it in another context, it would not be subject 
to copyright. I think they did a pretty good job trying to 
strike that balance.
    Chair Coons. In the conversation I had previously with 
Professor Sag, how do you feel about the scope of potential 
remedies if we were to craft an anti-impersonation statute?
    Mr. Harleston. I am glad you asked me that question.
    Chair Coons. I thought you'd be.
    [Laughter.]
    Mr. Harleston. Thank you. I think there should be a private 
right of action. I think that it is--I think commerciality is, 
again, not always the proper standard here.
    I think that in some instances we have had artists who have 
had been victim of deepfakes where the voice was appropriated, 
and the lyric content was something the artist would never have 
said.
    And that is something that can have irreparable harm to 
their career, you know, in trying to explain that it wasn't 
them, because there is stuff that is really good, these--sort 
of these AI-generated things are really good.
    Chair Coons. Ms. Ortiz, last but not least, has, in 
producing some of the interesting, engaging, powerful, 
inspiring content you have generated, have you ever relied on 
an AI tool to help you expand or produce some of the works you 
have worked on? And what is your hope about what we might do 
going forward here in Congress in response to what we have 
heard from you about your concerns?
    Ms. Ortiz. I am very happy you asked this question, 
Senator. So, I have never really--I was curious very early on 
before I knew the extent of the exploitation of artists. Very 
briefly used an AI to generate references, and I didn't enjoy 
it at all. I am--you know, I love every step of the process of 
being an artist.
    And ever since I found out, you know, last August, 
September, of what actually went behind the scenes, I just--I 
cannot use it. My peers refuse to use it. My industry is very 
clear that we do not want to exploit each other. And again, it 
is important to remember that these, you know, models basically 
compete in our own market.
    And this isn't something that is hypothetical. It has 
happened now with our own works. And one of the things that I 
would hope, you know, would be kind of addressed here is that a 
lot of the solutions that have been proposed--or, you know, 
basically you cannot enact them unless you know what is in the 
dataset.
    And for this, we need to ensure that there is clear 
transparency built from ground up. Like, no offense to some of 
the companies here, but if you don't know what exactly is in 
the dataset, how do we know?
    How does the licensor know that my work is in the dataset? 
And that I feel like it is one of the starting foundations for 
artists and other individuals as well to be able to gain 
consent, credit, and compensation.
    Chair Coons. Thank you. Mr. Tillis, before I just hand it 
over to you, and then we are going to conclude, I just 
appreciate all of you taking the time and effort helping 
educate us. You are literally training us as we try to produce 
some fidelity in our legislative work. Senator Tillis.
    Senator Tillis. Yes, to me, trying to figure out what may 
or may not be in the language model is a lot like taking roll 
in a dark classroom. I just don't understand how you would do 
it. So, you know, I can see that we have to work at it.
    But I want to start, Mr. Brooks, by thanking you for being 
here. I think that anyone that is watching this needs to 
understand that this isn't unique to Stability AI. This is a 
broader set of issues that we have to deal with, and I 
appreciate the fact that you'd be willing to come here because 
you should expect that some of the concerns are--that were 
going to be expressed to begin with.
    I have one question. The bad news for you all is that my 
staff are really excited about this. These are the questions 
[papers are shown to the witnesses]----
    [Laughter.]
    Senator Tillis [continuing]. That we are going to submit 
for the record. But rather than expect you all to respond to 
every one of them, you are welcome to do that, your area of 
expertise, your priorities, just use that to guide you, and get 
that information back for the record.
    But one of the ones I won't have to ask because I will ask 
it now is, a recent survey on how consumers view AI found that 
most consumers, nearly 80 percent, believe the use of AI should 
be explicitly disclosed.
    Now, in Vilnius, I happened to stay at a hotel that is 
called the Shakespeare Hotel, and every room was named after 
the greats. I don't see a day 100 hundred years from now where 
those rooms are going to be named after great LLMs. And the 
reason for that is I think there is a natural cultural bias for 
rewarding the human beings who are truly the creators and the 
lifeblood of our creative community.
    So, does anyone here disagree that a work that is derived 
even from, let's say, licensed content, that the consumer 
should know that this was created by a machine versus an 
original creative work by human beings?
    Anybody disagree with that, or maybe technical issues I 
should look at? No different than Mr. Rao, me, I use Photoshop. 
I could create Corvette cat with a skateboard or surfboard 
really quickly. No different than I want that, which, as you 
know, again, based on prior creative work, somehow have 
disclosures. Does that make sense to you?
    Mr. Rao. Yes, I think the question, and we thought about, 
we think it is definitely of interest to our creative 
customers, is to be able to show something human created versus 
AI created. In Adobe Firefly, it all comes out saying something 
is AI created.
    That is on by default. So, you will always know that it is 
AI created. The trick going forward, though, is we anticipate 
our AI features are our most popular features in Photoshop, so 
we expect going forward, most images are going to have a part 
that is AI and a part that is human, and you sort of have to 
start thinking about what are you disclosing when you disclose 
that. Right?
    The content credential we mentioned before that you could 
use a ``Do Not Train'' tag on it, or you could use it for, you 
know, addressing deepfakes. Also, we will record the human part 
versus the AI part. So, you could think about using that as a 
disclosure.
    But I am not sure over time people are going to be as 
interested in knowing the identity of the artist who created 
the work as opposed to which part of it they did with AI, and 
which----
    Senator Tillis. That is fair. Professor Sag, do you have a 
comment?
    Professor Sag. Just to follow up on that. You also have to 
think that you are not just talking visual works here. Like 
take the same thing with written works. Someone uses GPT to 
help smooth over their writing, refine something, explain it 
more clearly.
    There are some awkward line drawing questions, but the 
spirit of the disclosure requirement is correct. The 
implementation, I think, just will be difficult.
    Senator Tillis. I agree. And Mr. Chair, I am checking the 
votes. I think it is probably time for us to wrap up the 
Committee. I think you could see from this just by the sheer 
number of Members who came to the Subcommittee, this is an area 
of interest and a priority for us.
    Mr. Chair, I have decided that maybe for the next hearing, 
it is going to take a little bit more tuning for me to get the 
answer, but I am going to do a--with the--you know the song, 
``Who Let the Dogs Out''?
    [Laughter.]
    Senator Tillis. I was thinking we would set that to ``Don't 
steal my IP,'' and I will see if I can get that done. If you 
think about it, it'd be pretty snappy.
    [Laughter.]
    Senator Tillis. But I will work on that for those of you--
you may have to get a bigger room if people know about that in 
advance.
    Chair Coons. We may end up doing this as a duet.
    [Laughter.]
    Senator Tillis. But again, I think this Committee has 
demonstrated that we are very thoughtful, and we are very 
diligent, and I, for one, could sit at that table and probably 
present the interests of either side of the spectrum, which is 
why I believe that we need legislative certainty.
    We need to learn like data privacy, data ownership. In 
Europe, they don't always get it right in the first tranche, so 
we wouldn't necessarily lift something up and implement it 
here, but we want to think it through and make sure it is 
something that scales properly. But this is clearly an area 
where I don't think anyone--they would be hard pressed to 
convince me that no action is required.
    And again, my bias on this Committee from the beginning, 
having grown up in innovation, technological innovation, seeing 
the compelling numbers about how important it is to our economy 
and our culture, there is a lot of work to do.
    And I am confident with the leadership of the Chair, we are 
going to get work done. We look forward to your continued 
engagement. Thank you.
    Chair Coons. Thank you, Senator Tillis. I think it was Mr. 
Brooks, I may be wrong, who early on said that other 
technological developments, perhaps it was you Professor, word 
processing didn't end authorship, smartphones didn't end 
photography, but they impacted them. They impacted them.
    And we need to closely, and with some deliberation, realign 
what Federal rights and protections there are, both to deal 
with things like deepfakes--some argue that Shakespeare himself 
was a deepfake--to protect the rights of individuals, protect 
the rights of those who earn their living by being creative, to 
ensure that consumers understand what they are consuming, and 
to make sure that we are aligning with other countries that 
share our core values and our priority on a free market and the 
rights of individuals in contrast to other countries with other 
systems.
    So, I am grateful to all of you for testifying today, for 
taking your time and contributing to this. These are very 
challenging questions. Members can submit questions for the 
record for these witnesses if they were not able to attend. 
Questions for the record are due by 5 p.m., one week from 
today, July 19th.
    Again, thank you, all. I look forward to your input as we 
try and craft a good legislative solution. With that, this 
hearing is adjourned.
    [Whereupon, at 4:40 p.m., the hearing was adjourned.]
    [Additional material submitted for the record follows.]

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