    [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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