    [Senate Hearing 118-686]
    [From the U.S. Government Publishing Office]

                                                            S. Hrg. 118-686

                     ARTIFICIAL INTELLIGENCE IN GOVERNMENT

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

                                    HEARING

                                   before the

                                  COMMITTEE ON
                             HOMELAND SECURITY AND
                              GOVERNMENTAL AFFAIRS
                              UNITED STATES SENATE

                        ONE HUNDRED EIGHTEENTH CONGRESS

                                 FIRST SESSION
                                   __________

                                  MAY 16, 2023
                                   __________

            Available via the World Wide Web: http://www.govinfo.gov

                           Printed for the use of the
            Committee on Homeland Security and Governmental Affairs

                  [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

                       U.S. GOVERNMENT PUBLISHING OFFICE

    52-785 PDF                 WASHINGTON : 2025

            COMMITTEE ON HOMELAND SECURITY AND GOVERNMENTAL AFFAIRS

                       GARY C. PETERS, Michigan, Chairman
    THOMAS R. CARPER, Delaware           RAND PAUL, Kentucky
    MAGGIE HASSAN, New Hampshire         RON JOHNSON, Wisconsin
    KYRSTEN SINEMA, Arizona              JAMES LANKFORD, Oklahoma
    JACKY ROSEN, Nevada                  MITT ROMNEY, Utah
    ALEX PADILLA, California             RICK SCOTT, Florida
    JON OSSOFF, Georgia                  JOSH HAWLEY, Missouri
    RICHARD BLUMENTHAL, Connecticut      ROGER MARSHALL, Kansas

                       David M. Weinberg, Staff Director
                        Zachary I. Schram, Chief Counsel
                      Michelle M. Benecke, Senior Counsel
                            Evan E. Freeman, Counsel
               William E. Henderson III, Minority Staff Director
                  Christina N. Salazar, Minority Chief Counsel
                      Andrew J. Hopkins, Minority Counsel
              Kendal B. Tigner, Minority Professional Staff Member
                         Laura W. Kilbride, Chief Clerk
                       Ashley A. Gonzalez, Hearing Clerk

                                C O N T E N T S

                                    ------
    Opening statements:
                                                                       Page
        Senator Peters...............................................     1
        Senator Paul.................................................     3
        Senator Lankford.............................................    18
        Senator Scott................................................    20
        Senator Hassan...............................................    23
        Senator Rosen................................................    25
        Senator Padilla..............................................    28
        Senator Ossoff...............................................    31
    Prepared statements:
        Senator Peters...............................................    37
        Senator Paul.................................................    39

                                   WITNESSES

                             TUESDAY, MAY 16, 2023

    Lynne E. Parker, Ph.D., Associate Vice Chancellor and Director,
      AI for Tennessee Initiative, University of Tennessee...........     5
    Taka Ariga, Chief Data Scientist, U.S. Government Accountability
      Office.........................................................     7
    Daniel E. Ho, Professor, Stanford Law School.....................     8
    Richard A. Eppink, of Counsel, American Civil Liberties Union of
      Idaho Foundation...............................................    10
    Jacob Siegel, Writer.............................................    12

                         Alphabetical List of Witnesses

    Ariga, Taka:
        Testimony....................................................     7
        Prepared statement...........................................    48
    Eppink, Richard A.:
        Testimony....................................................    10
        Prepared statement...........................................    72
    Ho, Daniel E.:
        Testimony....................................................     8
        Prepared statement...........................................    66
    Parker, Lynne E.:
        Testimony....................................................     5
        Prepared statement...........................................    42
    Siegel, Jacob:
        Testimony....................................................    12
        Prepared statement...........................................    85

                                    APPENDIX

    Statement submitted for the Record by Association for Computing
      Machinery                                                         129
    Responses to post-hearing questions for the Record:
        Mr. Siegel...................................................   141

                     ARTIFICIAL INTELLIGENCE IN GOVERNMENT

                                  ----------

                             Tuesday, May 16, 2023

                                         U.S. Senate,
                               Committee on Homeland Security
                                      and Governmental Affairs,
                                                        Washington, DC.
        The Committee met, pursuant to notice, at 10 a.m., in room
    SD-562, Dirksen Senate Office Building, Hon. Gary Peters,
    Chairman of the Committee, presiding.
        Present: Senators Peters [presiding], Hassan, Sinema,
    Rosen, Padilla, Ossoff, Paul, Johnson, Lankford, Scott, Hawley,
    and Marshall.

                 OPENING STATEMENT OF SENATOR PETERS\1\

        Chairman Peters. The Committee will come to order.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Senator Peters appears in the
    Appendix on page 37.
    ---------------------------------------------------------------------------
        Today's hearing is the second in a series that I plan to
    convene on artificial intelligence (AI). At our first hearing
    in March, we discussed the transformative potential of AI, as
    well as the possible risks these technologies can pose. Today,
    we will be discussing how AI has the potential to help
    government better serve the American people, such as by
    improving the ways agencies deliver services and also what
    pitfalls we need to be aware of as government increasingly
    adopts AI.
        The Federal Government is already using AI in an effort to
    provide more efficient services, assess potential security
    threats, and automate routine tasks to enhance the Federal
    workforce.
        Earlier this month, the White House announced new efforts
    to invest in American leadership to develop AI technologies and
    promote the responsible use of AI within the Federal
    Government. Later this summer, the Office of Management and
    Budget (OMB) is expected to release new guidance on Federal
    Government use of AI, implementing legislation this Committee
    advanced in 2020, and was later signed into law in government
    funding legislation.
        U.S. leadership in the development and use of AI systems,
    by both the private sector and government, is essential for our
    global economic competitiveness. We should work to ensure that
    government can adopt and deploy these tools to help improve
    American lives, but as we do so we must ensure we are also
    prepared to address the potential risks and harms that AI
    systems can present.
        The potential for bias in AI applications can have serious
    consequences for Federal Government use. A recent study found
    that an algorithm used by the Internal Revenue Service (IRS) to
    determine who should be audited was erroneously more likely to
    recommend Black taxpayers than white taxpayers, and the
    government was not prepared with the data or training necessary
    to actually recognize this biased outcome.
        As we heard in our last hearing, AI algorithms often lack
    transparency and accountability for how they arrive at certain
    outcomes. Even the engineers who design them do not always
    understand how they reach the conclusions that they reach.
        In government applications, this can present serious risks
    to Americans who may unknowingly be interacting with an AI, and
    who may struggle to get answers about why an AI system made a
    certain determination.
        For example, at least a dozen States deployed algorithms to
    decide eligibility for disability benefits, which resulted in
    denying thousands of recipients this critical assistance that
    helped them live independently, and left them with little
    opportunity to understand why the decision was made or how they
    could possibly appeal it.
        The enormous amounts of data that can be collected as a
    result of using AI systems also presents concerns about
    privacy. Existing privacy laws do not envision these types of
    applications.
        As agencies use more AI tools, they will need to ensure
    they are securing and appropriately using any data inputs to
    avoid accidental disclosures or unintended uses that harm
    Americans' civil rights or their civil liberties.
        Finally, we must ensure our Federal workforce is ready to
    procure and oversee the use of AI systems to ensure they are
    benefiting Americans. Last Congress, I authored legislation
    that was signed into law requiring officials charged with
    procuring AI tools to be trained in both their capabilities to
    improve agency missions, and their potential risks, to ensure
    responsible use.
        Last week, I introduced bipartisan legislation to build on
    that effort by requiring Federal agency supervisors and
    managers to receive similar training.
        I am looking forward to today's discussion and to
    continuing to work with my colleagues on both sides of the
    aisle to advance solutions that will help encourage American
    development of AI, and ensure it is being used appropriately.
        During today's hearing, we will be discussing some of those
    strategies, including the need to conduct inventories of
    current Federal Government AI applications, requiring ongoing
    audits to ensure the accuracy and effectiveness of AI systems,
    and considering responsible standards that need to be met as
    the Federal Government continues to acquire additional AI
    tools.
        I am grateful to our expert witnesses for joining us today.
    We look forward to a fruitful discussion, and a discussion that
    will likely continue well beyond this hearing and be engaging
    for the foreseeable future.
        I would now like to recognize Ranking Member Paul for his
    opening statement before we hear from our witnesses. Ranking
    Member Paul.

                  OPENING STATEMENT OF SENATOR PAUL\1\

        Senator Paul. In 1975, the late Senator Frank Church said,
    ``The United States government has perfected a technological
    capability that enables us to monitor the messages that go
    through the air. That capability at any time could be turned
    around on the American people, and no American would have any
    privacy left, such is the capability to monitor everything.
    There would be no place to hide.''
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Senator Paul appears in the Appendix
    on page 39.
    ---------------------------------------------------------------------------
        These words came as Senator Church led the Senate Select
    Committee to Study Governmental Operations with Respect to
    Intelligence Activities, better known as the Church Committee.
        The Church Committee's 1976 final report exposed numerous
    secret Federal programs that violated the constitutional rights
    of American citizens it deemed to be threats to existing social
    and political order. These programs surveilled and targeted
    individuals like Martin Luther King Jr. and domestic
    organizations like the Southern Christian Leadership
    Conference, as well as infiltrated movements to incite
    rivalries and discredit leaders.
        Nearly 50 years later, Senator Church's ominous warning
    that the government could weaponize technology against the
    American people reads more like a premonition. There is truly
    becoming ``no place to hide.''
        In recent decades, journalists and whistleblowers exposed
    examples of our government leveraging emerging technologies to
    violate the privacy and civil liberties of its citizens.
        Intelligence agencies conducted surveillance of video game
    users, collecting data on the contents of communications
    between players.
        The Department of Homeland Security (DHS) tracked the
    locations of individuals and groups participating in the Black
    Lives Matter (BLM) movement.
        The Drug Enforcement Administration (DEA) conducted
    ``covert surveillance'' of people protesting the death of
    George Floyd.
        It is only getting worse. Just last month, the American
    Civil Liberties Union (ACLU) acknowledged, ``The Biden
    administration has been quietly deploying and expanding
    programs that surveil what people say on social media, using
    tools that allow agents and analysts to invisibly monitor the
    vast amount of protected speech that occurs online.''
        How are they doing it? Using artificial intelligence.
        For years, Federal agencies, including the Department of
    Homeland Security, State Department (DOS), National Science
    Foundation (NSF), and the Federal Bureau of Investigation (FBI)
    have been colluding with private organizations and social media
    companies to combat what they deemed to be ``disinformation.''
    Jacob Siegel, in ``Tablet,'' wrote, ``Disinformation is both
    the name of the crime and the means to covering it up, a weapon
    that doubles as a disguise.'' I think that is an apartment way
    of looking at disinformation. It is a tool for those who want
    to limit speech, but it also doubles as a disguise and a means
    of covering up what they are actually trying to do.
        The purpose, so they claimed, was to combat foreign malign
    influence. But in reality, the government was not suppressing
    foreign ``misinformation.'' It was working to censor domestic
    speech by Americans.
        Since 2020, the Federal Government has awarded over 500
    contracts and grants related to ``misinformation'' or
    ``disinformation.'' George Orwell would be proud. While the
    grant awardees and their proprietary AI and machine learning
    technologies differ, their goals are consistent: to ``mine''
    the internet, identify conversations indicative of ``harmful''
    narratives, track those ``threats,'' and develop
    countermeasures before messages go viral. One National Science
    Foundation-funded company's mission statement claims that
    ``social media is being manipulated and ideas are being spread
    uncontrollably online.''
        The solution it provides? An automatic controversy
    detection algorithm to help identify things that are
    ``potentially opinion-shifting'' in order to make communication
    ``more productive and less dangerous,'' in other words,
    censorship.
        During the Coronavirus Disease 2019 (COVID-19) pandemic, we
    witnessed the accelerated use of artificial intelligence
    technologies to monitor and suppress public debate on issues
    like natural immunity, masks, and the origin of the virus.
    Multiple Federal agencies, including the Department of Defense
    (DOD) and the State Department, funded automated
    disinformation-detection technologies designed to monitor and
    suppress public debate on issues like vaccines and the origins
    of COVID-19.
        Writer Jacob Siegel, in a fantastic, yet haunting,
    narrative explaining the last decade of U.S. Government
    domestic censorship efforts said, ``Disinformation, now and for
    all time, is whatever they say it is. That is not a sign that
    the concept is being misused or corrupted; it is the precise
    functioning of a totalitarian system.''
        Make no mistake. The United States is engaging in the same
    activities we criticize other countries for. But unlike China
    and North Korea, the United States government attempts to
    conceal its involvement using private entities as front
    companies to do its dirty work.
        But make no mistake. The intent is the same. Control the
    narrative, eliminate dissent, and retain power.
        This should terrify all Americans. The government is using
    your hard-earned tax dollars to surveil and censor your
    protected speech. Artificial intelligence is only going to make
    it easier for the government to do this, and harder to detect.
        This should not be a partisan issue. We must get to the
    bottom of how the Federal Government uses AI to violate the
    privacy and civil liberties of the American people before it is
    too late.
        Chairman Peters. Thank you, Ranking Member Paul.
        It is the practice of the Homeland Security and
    Governmental Affairs Committee (HSGAC) to swear in witnesses,
    so if each of you would please stand and raise your right hand.
        Do you swear that the testimony that you will give before
    this Committee will be the truth, the whole truth, and nothing
    but the truth, so help you, God?
        Mr. Eppink. I do.
        Mr. Ariga. I do.
        Dr. Parker. I do.
        Mr. Ho. I do.
        Mr. Siegel. I do.
        Chairman Peters. Thank you. You may be seated.
        Our first witness is Dr. Lynn Parker. Dr. Parker is the
    Associate Vice Chancellor and Director of the AI Tennessee
    Initiative at the University of Tennessee (UT). Dr. Parker
    spent four years as Deputy United States Chief Technology
    Officer (CTO) and Director of the National AI Initiative Office
    (NAIIO) within the White House Office of Science and Technology
    Policy (OSTP).
        Before joining OSTP in 2018, Dr. Parker served as the
    interim Dean of the University of Tennessee's Tickle College of
    Engineering. She has also served as the National Science
    Foundation's Division Director for Information and Intelligence
    Systems.
        Dr. Parker, welcome to the Committee. We look forward to
    hearing your opening statement.

        TESTIMONY OF LYNNE E. PARKER, PH.D.,\1\ ASSOCIATE VICE
         CHANCELLOR  AND  DIRECTOR,  AI  FOR TENNESSEE INITIA-
         TIVE, UNIVERSITY OF TENNESSEE

        Dr. Parker. Thank you so much. Chairman Peters, Ranking
    Member Paul, and Members of the Committee, thank you for
    inviting me to testify at this hearing on AI in government. I
    am Associate Vice Chancellor at the University of Tennessee,
    Knoxville, and Director of the AI for Tennessee Initiative,
    where we are working to establish Tennessee as a leader in the
    data-driven knowledge economy.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Dr. Parker appears in the Appendix on
    page 42.
    ---------------------------------------------------------------------------
        My remarks today focus on ways that Federal agencies can
    better leverage and govern the responsible use of AI in
    advancing their missions and providing services to the American
    people.
        Federal uses of AI are becoming increasingly transparent as
    agencies make available their AI use case inventories in
    compliance with Executive Order (EO) 13960 and the Advancing
    American AI Act. The extreme variety of Federal AI use cases
    creates challenges for developing a flexible approach to the
    responsible governance and use of AI by the Federal Government.
        To help accelerate the responsible governance and use of AI
    in government, I offer the following recommendations.
        First, as directed by the AI in Government Act of 2020, and
    Executive Order 13960, OMB should prioritize and adequately
    resource their work on creating Federal guidance for the use of
    AI in government. This guidance should address the wide
    diversity of use cases of AI across the Federal Government,
    encourage the responsible adoption of AI to improve public
    services while protecting privacy, civil rights, and civil
    liberties, and be operational for use by the agencies.
        Second, Congress should require Federal agencies to use the
    National Institute of Standards and Technology (NIST) AI Risk
    Management Framework (RMF) during the design, development,
    procurement, use, and management of AI. Beginning with a
    standardized assessment of the risks posed by use cases of AI
    is a key step that can be taken now by all Federal agencies
    without needing to wait for additional OMB guidance.
        Third, Congress should require every Federal agency to have
    a current and regularly updated AI strategic plan that includes
    that agency's approach to the responsible adoption of AI.
        Fourth, Congress should direct each agency to hire and
    resource a Chief AI Officer (CAIO) who is responsible for
    overseeing the development and regular update of the
    organization's AI strategy and use of AI.
        Fifth, Congress should direct the creation of an
    interagency Chief AI Officers Council as an effective way to
    coordinate the governance and use of AI within the Federal
    Government.
        Sixth, the proposed Chief AI Officer's Council should
    review the agency AI use case inventories for common
    application areas and identify dozens of key agency processes
    that could be transformed with AI, in a manner consistent with
    privacy, civil rights, and civil liberties.
        Seventh, Congress should accelerate the responsible and
    innovative adoption of AI by providing agencies with AI
    innovation funds as part of their annual operating budgets.
        Eighth, to help address AI workforce shortages in the
    Federal Government, and as directed by the AI in Government Act
    of 2020, the Office of Personnel Management (OPM) should
    prioritize and adequately resource their work on the AI
    occupational series so that Federal agencies will be better
    positioned to strengthen their AI workforces.
        Ninth, Congress should direct the development of a National
    Initiative for AI Education Framework, analogous to the NIST
    National Initiative for Cybersecurity Education (NICE),
    Framework, that was developed in 2017, to provide a
    comprehensive and standardized approach to describing AI roles
    and the associated knowledge, skills, and abilities needed for
    those roles.
        Finally, to help strengthen the breadth and diversity of
    talent in the nation's AI ecosystem, Congress should authorize
    and fund the National AI Research Resource, as proposed by the
    congressionally directed National AI Research Resource Task
    Force. Such a resource would help develop new AI talent, with
    some of this talent likely choosing to use their AI skills to
    support the Federal Government in its adoption and governance
    of responsible AI.
        I thank the Committee for the opportunity to testify and
    look forward to your questions.
        Chairman Peters. Thank you. Thank you, Dr. Parker.
        Our next witness is Taka Ariga. Mr. Ariga is the Chief Data
    Scientist and Director of the Innovation Lab at the U.S.
    Government Accountability Office (GAO). As an integral part of
    the Science, Technology, Assessment, and Analytics team, he
    helps GAO develop and implement advanced analytical
    capabilities for its auditing processes.
        Prior to joining GAO, he held executive positions at
    Deloitte, Ernst & Young and Booz Allen Hamilton, where he
    worked with audit, compliance, legal, and regulated entities.
        Welcome to the Committee, and we look forward to your
    testimony.

        TESTIMONY OF TAKA ARIGA,\1\ CHIEF DATA SCIENTIST, U.S.
                   GOVERNMENT ACCOUNTABILITY OFFICE

        Mr. Ariga. Chairman Peters, Ranking Member Paul, and
    distinguished Members of the Committee, thank you for inviting
    me to participate in today's hearing on artificial intelligence
    in the Federal Government.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Mr. Ariga appears in the Appendix on
    page 48.
    ---------------------------------------------------------------------------
        As GAO's Chief Data Scientist and Director of our
    Innovation Lab, I see AI's potential in action every day. But
    as you noted in your March 8th hearing, significant risks and
    challenges exist wherever AI is assisting or replacing
    discretionary decisionmaking.
        AI is undeniably an integral part of a functioning digital
    fabric. However, the Federal Government is certainly not immune
    from consequences of this powerful technology. The need to
    promote responsible and accountable use of AI is even more
    striking now in the face of growing dangers from unfair,
    unintended, or misleading outcomes that carry cascading
    societal impacts.
        Paradoxically, agencies continue to face acute short of
    Federal digital talent needed to implement accountability
    practices. We must address both challenges at pace with, and
    perhaps even anticipate, rapid advances in AI capabilities.
        GAO has issued more than two dozen reports over the past
    several years to promote responsible and accountable use of AI.
    One of the most notable moments is the introduction of our AI
    Accountability Framework in summer of 2021. This first-of-its-
    kind blueprint moved beyond high-level aspirations and laid out
    33 key implementation practices across four pillars for Federal
    agencies to consider as they navigate the AI development
    lifecycle. In this framework, we also stress the importance of
    taking a team sport approach that integrates perspectives from
    an ecosystem of stakeholders.
        Beyond GAO's own use across our audit engagements, we are
    seeing adoption of the framework by the broader oversight
    community to conduct AI evaluations.
        On the workforce front, GAO has steadfastly reported on
    mission-critical gaps for Federal expertise in science and
    technology (S&T) since 2001. The Federal Government, as a
    whole, continues to face barriers in hiring, managing, and
    retaining staff with advanced technical skills, the very skills
    needed to design, develop, deploy, and monitor AI systems.
        In our November 2021 report, GAO gathered perspective from
    technology leaders across Federal, academic, and nonprofit
    entities to explore the concept of establishing a U.S. Digital
    Services Academy (USDSA). The aim is to improve the Federal
    pipeline of highly trained digital talent that can effectively
    and responsibly modernize government, including implementation
    of AI systems. Ultimately, having a robust cadre of a digital-
    ready, Federal workforce ensures humans can successfully remain
    in, and never out of the AI loop.
        GAO remains committed to supporting Congress on the ``trust
    but verify'' part of the AI accountability equation. We have
    formed an internal AI community of practice that includes every
    GAO mission team. We have established internal training
    resources to enhance data literacy and data science. We have
    hired more data scientists. Our Innovation Lab is actively
    exploring a variety of impactful machine learning techniques to
    transform audit function. We remain engaged with a network of
    oversight partners, academic, and governmental entities at all
    levels to exchange insights. All of these efforts give GAO
    hands-on experience to stay at the forefront of AI technology,
    with which to offer technical assistance and strengthen
    oversight capacity.
        Realizing accountable AI is a continuing journey that
    requires a whole-of-government approach, Federal agencies need
    more specific guidance on effective implementation of AI. At
    the same time, we need practical policy solutions that address
    interconnected challenges on privacy, civil liberties, and
    workforce readiness.
        We know AI capabilities will evolve at an incredible speed,
    and the use of AI will continue to diffuse across facets of
    governmental functions. GAO believes that the Federal
    Government can, and must, simultaneously realize opportunities
    afforded by AI and be leaders in good governance, transparency,
    and compliance in this age of algorithmic renaissance.
        Chairman Peters, Ranking Member Paul, and Members of the
    Committee, this concludes my prepared statement. I will be
    happy to answer any questions you may have.
        Chairman Peters. Thank you, Mr. Ariga.
        Our next witness is Professor Daniel Ho. Professor Ho is
    the William Benjamin Scott and Luna M. Scott Professor of Law
    at Stanford Law School, Professor of Political Science, Senior
    Fellow at the Stanford Institute for Economic and Policy
    Research, Associate Director of the Stanford Institute for
    Human-Centered Artificial Intelligence (HAI), and Director of
    the Regulation, Evaluation, and Governance Lab. He also serves
    on the National Artificial Intelligence Advisory Commission and
    is a Senior Advisor on Responsible AI to the Department of
    Labor (DOL).
        Professor, welcome to the Committee. We look forward to
    your opening remarks.

         TESTIMONY OF DANIEL E. HO,\1\ PROFESSOR, STANFORD LAW
                                SCHOOL

        Mr. Ho. Chairman Peters, Ranking Member Paul, and Members
    of the Committee, it is an honor to speak with you today.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Mr. Ho appears in the Appendix on
    page 66.
    ---------------------------------------------------------------------------
        The youth government has an exceptional opportunity. It can
    seize this moment of AI innovation to modernize Federal
    programs, catalyze scientific advancements, and protect the
    rights and benefits of all Americans. Doing so will strengthen
    America, but strategic leadership, Federal workforce
    investments, digital infrastructure, and procurement
    modernization will be necessary. The Federal Government needs
    to go from having a few pockets of innovation to a culture of
    innovation.
        Let me start with why AI in government matters so much.
    First, government should lead by example and demonstrate how
    responsible AI can modernize Federal programs. In a report we
    showed how early AI innovation in nearly half of the largest
    140 Federal agencies can transform Veterans Benefits
    Administration (VBA), improve monitoring of adverse drug
    events, and help protect workers, consumers, and the
    environment.
        Take the Social Security Administration (SSA), which can
    hear over half a million disability appeals per year. With
    great foresight, SSA began investing in data infrastructure and
    tools to modernize case adjudication in the 1990s. This
    culminated in an AI tool that allows judges to use natural
    language processing to check draft decisions for some 30
    errors, accelerating and improving case processing, leaving
    some to call the official who pioneered these early investments
    the ``Steve Jobs of the SSA.''
        Second, government agencies are, of course, critical for
    effective regulation of the risks of AI, and striking the right
    balance between innovation and safeguards requires expertise in
    government. Getting technical talent into the Federal workforce
    is the single biggest obstacle for effective regulation.
    Government cannot govern AI if it does not understand AI.
        While much progress has been made, including legislation
    from this Committee, we still have a long way to go. When our
    research team at Stanford examined the implementation of AI-
    related legal requirements, stemming from two Executive Orders
    and the AI in Government Act, we found a critical gap in
    leadership, strategic planning, and capacity. For instance, 88
    percent of agencies failed to submit AI plans to identify
    regulatory authorities, and the implementation of a key
    transparency measure, agency disclosure of AI use cases, has
    been inconsistent, and the Office of Personnel Management has
    yet to release a required report, due July of last year, to
    forecast the AI employment needs and to create an AI hiring
    line.
        This must change. The Federal workforce does herculean work
    but faces fundamental challenges developing teams that can
    design, implement, and regulate AI effectively and responsibly.
    Stanford's HAI's AI Index highlights that 65 percent of AI
    Ph.D.'s land in industry, 28 percent in academia, and less than
    two percent in government. Or in the words of one entrepreneur,
    ``The best minds of my generation are thinking about how to
    make people click on ads.''
        Strengthening the pipeline of technical talent into the
    public sector and providing career paths is urgent. As the
    National Security Commission on AI noted, it is not just
    compensation. ``It is the perception, and too often the
    reality, that it is difficult for digital talent in government
    to perform meaningful work.'' I have seen this firsthand. One
    Stanford AI Ph.D. student became so frustrated by an agency's
    decades-old software stack and lack of computing resources that
    he gave up on his aspirations for a career in government and
    went back to work in industry.
        Let me conclude with four recommendations.
        First, strategic leadership from the Federal Government is
    required to coordinate and drive forward trustworthy AI
    innovation. Congress should borrow a page from the bipartisan
    Evidence Act and empower chief AI Officers to ensure that
    senior leadership within agencies is driving forward
    responsible AI innovation and oversight.
        Second, Congress should establish new pathways and
    trajectories for technical talent in government. We need better
    models--building on the U.S. Digital Service (USDS), public-
    private partnerships, and academic-agency partnerships--to
    attract AI talent to public service, build cross-functional
    teams, and provide pathways for career advancement.
        Third, government procurement is critical to capitalize on
    American innovation and spur developments of rights-preserving,
    privacy-enhancing technologies. We need to move toward more
    modular forms of contracting, which the Department of Defense
    has illustrated, that enables more effective development,
    acquisition, assessment, and auditing of AI systems.
        Last, we have to invest in digital infrastructure,
    including the National AI Research Resource, endorsed by
    multiple Federal task forces, for secure access to
    administrative data and large-scale computing resources to
    level the playing field. Government data, which is higher
    quality, more representative, and reliable than web data that
    many models are trained on, is an important part of the
    solution. When the U.S. Geological Service (USGS) made Landsat
    satellite imagery free to researchers in 2008, it generated $3
    to $4 billion in benefits annually, catalyzing discoveries in
    habitat modification, climate change, and poverty. That is the
    promise of getting public sector innovation right.
        The U.S. Government should act expeditiously to foster
    responsible AI adoption.
        I am looking forward to your questions.
        Chairman Peters. Thank you. Our next witness is Ritchie
    Eppink. Mr. Eppink serves as Counsel for the American Civil
    Liberties Union of Idaho Foundation. He was previously the
    Justice Architect for the Idaho Legal Aid Services, and before
    that a Fulbright Fellow.
        Mr. Eppink, you are recognized for your opening statement.

           TESTIMONY OF RICHARD A. EPPINK,\1\ OF COUNSEL,
         AMERICAN CIVIL LIBERTIES UNION OF IDAHO FOUNDATION

        Mr. Eppink. Thank you, Chairman Peters, Ranking Member
    Paul, and Committee Members for your attention to artificial
    intelligence and automated decisionmaking in government
    programs.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Mr. Eppink appears in the Appendix on
    page 72.
    ---------------------------------------------------------------------------
        I was invited here today because I have been working for
    over a decade with Idahoans with developmental disabilities and
    their families to challenge secret decisions made by
    computerized algorithmic systems. Only through litigation that
    I have helped these families pursue were they able to access
    the algorithms the State of Idaho uses to make decisions about
    the health care that they depend on day to day.
        Once we opened the black box that concealed that automated
    system, we found that it was built out of corrupt data, relied
    on inputs that the State never validated, and produced results
    that even those who created it could not explain. A Federal
    court ruled that the system was unconstitutional.
        Yet a decade after filing suit and over seven years since
    winning in court we are still litigating the case, battling for
    due process against still more black box secrecy. Decades-long
    class actions by indigent families are not a viable plan for AI
    governance in taxpayer programs. We need Federal regulation and
    enforcement to protect basic fairness and constitutional rights
    in government programs that use AI in automated decisionmaking
    systems.
        A little bit about the Idaho lawsuit. Although in the past
    our society shamefully confined people with developmental
    disabilities in State hospitals, today, through Medicaid, they
    can get services at home and in their communities instead, at a
    savings to the government and to taxpayers.
        One of my clients was Christie Mathwig. She was a bulwark
    in her rural community of Troy, Idaho, a mother, and a leader
    in her church, bible studies, and Al-Anon. She was also
    diagnosed as a teenager with a rare neuromuscular disease and
    relied on workers in her community for health care and support
    throughout her day. Each year, the State assigned her a budget:
    not dollars that she would ever see, but reimbursement for her
    health care providers, based on assessment results plugged into
    an automated system.
        Christie came to me when the State told her her budget
    would suddenly be cut by tens of thousands of dollars, more
    than 20 percent, and not enough for the 24-hour support she
    needed to survive. The State refused to provide an explanation,
    claiming that the system was a ``trade secret.''
        We filed suit, and a Federal court quickly ordered the
    agency to disclose the system to us. It turned out to be just a
    handful of formulas coded into a basic Microsoft Excel
    spreadsheet. As rudimentary as it was, it still took us many
    months, three experts, and over $40,000 to reverse-engineer the
    system, catalog its flaws, and assess the harm that its results
    could wreak upon our clients. We presented our analysis to the
    court, and it ruled that the system arbitrarily deprives
    participants of their property rights and, hence, violates due
    process.
        I want to point out three dangers with automated government
    decisionmaking that this Idaho litigation, which is known as
    the K.W. v. Armstrong lawsuit, illustrates, and then I want to
    share three solutions that Congress should enmesh across
    Federal programs like these.
        First, the dangers. One, black boxes that conceal
    government use of AI. If my clients had not found a lawyer with
    the time and resources to help, they probably still would not
    know that Idaho was using an automated system to make decisions
    about them in the first place.
        Two, black boxes concealing how these systems work,
    including bad data that they are trained on. Once a Federal
    court order put Idaho's secret formulas into our hands, it took
    a mammoth effort to figure out all the many things that were
    wrong with it, including erroneous and corrupt data underlying
    it.
        Three, black boxes that prevent accountability. Idaho's
    Medicaid agency has been fighting again and again, including
    just last month, to ban my clients from accessing the very
    information they need to challenge the results of its automated
    system.
        Now toward solutions. There are three that I want to stress
    today.
        First, the people that these AI systems make decisions
    about should be integrally involved in their development,
    implementation, and evaluation. This is a cornerstone of the
    court-ordered settlement agreement in the Idaho case, and it is
    the solution that could prevent the most dangers.
        Two, government agencies must implement constitutional
    rights through regulation and enforcement specific to AI
    systems. Case-by-case litigation, which we know from Idaho is
    immensely resource intensive, is not a sustainable solution.
        Three, transparency requirements and governance standards
    must apply to these systems from before they start until after
    they finish. Black boxes have plagued the Idaho system since
    2012, and continue through to the present, in 2023. My clients
    have a right to the same information the government does to
    evaluate these systems and to challenge their results, and
    private contractors' proprietary interests can never be allowed
    to trump individual due process and equal protection rights.
        Thank you for the opportunity to testify. I look forward to
    your questions.
        Chairman Peters. Thank you.
        Our final witness is Jacob Siegel. Mr. Siegel is a writer
    and senior editor of News and The Scroll for Tablet magazine.
    He previously covered national security and digital culture for
    the Daily Beast. His writing has been published in the New York
    Times, Politico, the New York Daily News, Vice, Rolling Stone,
    and the National Endowment for the Humanities magazine.
        Mr. Siegel, welcome. You may proceed with your opening
    comments.

                  TESTIMONY OF JACOB SIEGEL,\1\ WRITER

        Mr. Siegel. Good morning, Chairman Peters, Ranking Member
    Paul, and Members of the Committee. Thank you for the
    opportunity to testify. I am Jacob Siegel, a writer and senior
    editor at Tablet magazine as well as a former military
    intelligence officer and Iraq and Afghanistan veteran.
    ---------------------------------------------------------------------------
        \1\ The prepared statement of Mr. Siegel appears in the Appendix on
    page 85.
    ---------------------------------------------------------------------------
        Throughout history, warfare has spurred the development of
    transformative new technologies. My experiences in the war on
    terror provided me with a glimpse of the AI revolution that is
    remaking America's political system and culture in ways that
    have already proved incompatible with our system of democracy
    and self-government, and may soon become irreversible.
        I first encountered issues of artificial intelligence in
    governance when I was deployed to western Afghanistan in 2012.
    What I found there was that in the midst of a great deal of
    confusion and ambivalence about the U.S. mission and what we
    were still trying to accomplish after a decade at war, the
    military had turned to powerful new information technologies
    (IT) to fill the strategic void.
        On critical fronts like defeating the Taliban and standing
    up the Afghan Security Forces, our success remained illusory.
    But in the face of this systemic failure the United States
    developed a special capacity for building databases.
        The theory of data-driven warfare was that collecting
    enough information and marrying it with the proper algorithms
    into AIs that could perform predictive analysis opened a
    technical portal into the future. We could stop the next
    improvised explosive device (IED) attack before it occurred,
    control events on the ground, and win over the Afghans to our
    cause.
        It did not work out that way. Years before the United
    States withdrawal and the Taliban's return to power, I had come
    to see that the gap between our official metrics of success and
    the reality on the ground was not only a result of measuring
    the wrong things. By translating critical questions of politics
    and policy into the language of data, we had outsourced the
    most fundamental responsibility of statecraft to machines,
    while rendering the essential notions of war, victory, and
    peace, obscured to America's leaders.
        AI moves us at an exponential rate from obscurity to the
    impenetrable darkness of the so-called black box. As the
    computer scientist, Stephen Wolfram noted when he testified
    before the Senate in 2019, ``If we want to seriously use the
    power of computation and AI then inevitably there won't be a
    human explainable story about what is happening inside.''
        America was founded on the ideal that individual citizens,
    through their free and informed actions, should participate in
    their government. But for a free people to participate in the
    making of their own laws and the meaning of their own lives,
    they must be knowledgeable about the world around them.
    Centralized applications of AI that invisibly alter the
    architecture of perception and reality, for instance by
    performing mass censorship of certain phrases or narratives,
    makes such knowledge impossible.
        Moreover, as the writer, James Poulos, has noted, ``The AI
    approach to governance undermines individual's faith in their
    own capacity for reason to action because it is driven by a
    logic of seeing technology as better and stronger than
    humanity.''
        In other words, a technology that is intrinsically
    threatening to human interests, with a potential
    transformational power on the order of the printing press or
    the wheel, which is, at this moment, being funded and deployed
    by multiple government agencies, appears destined to move
    further away from human understanding the more it progresses.
    Yet there is no chance that the U.S. Government and U.S.-based
    corporations are going to abandon a technology this powerful,
    nor would such an outcome necessarily be desirable, given that
    it would cede the space to competitors like China.
        We seem to be caught in a trap. There is a vital national
    interest in promoting the advancement of AI, yet at present the
    government's primary use of AI appears to be as a political
    weapon to censor information that it or its third-party
    partners deem harmful.
        Example abound from recent years of this kind of AI-driven
    informational control system, which is deployed at every
    opportunity in the name of public safety and emergency. It is
    in the name of safety that government officials are now calling
    for even more control over AI.
        Earlier this month, Jen Easterly, the Director of the
    Cybersecurity and Infrastructure Security Agency (CISA) called
    for more regulation of AI, warning that we need to be very
    mindful of making some of the same mistakes with artificial
    intelligence that we have made with technology. But regulating
    AI so that it becomes an even more powerful tool of censorship
    for enforcing party orthodoxies will increase neither or safety
    nor our security.
        Easterly also recently argued that China has already
    established guardrails to ensure that AI represents Chinese
    values, and the United States should do the same. While
    emulation of the Chinese model of top-down, party-driven social
    control appears to be the direction that AI in governance are
    moving in the United States, I would submit, respectfully, that
    continuing in this direction will mean the end of our tradition
    of self-government and the American way of life.
        Thank you.
        Chairman Peters. Thank you, Mr. Siegel.
        Mr. Eppink, in your testimony you told us about how you are
    suing the Idaho Medicaid program for its failure to disclose
    the algorithm that it used to substantially cut recipients'
    health care services. But could you tell the Committee more
    about how your clients even learned about the use of this
    automated system?
        Mr. Eppink. Certainly, Chairman. The Idaho system, when we
    got started, I think like many other systems around the country
    probably still today, was not disclosed to anyone outside of
    the Idaho agency, so far as I know, and after about a half
    dozen families had contacted me, scared that their lives would
    be upended, I figured I would send a letter, which I did, and I
    got one back from the agency's lawyers saying that the system
    was a trade secret. Once we knew it was a secret, we had to go
    from there to file a lawsuit to find out more about what the
    system was.
        Chairman Peters. Right now we are hearing an awful lot
    about generative AI tools, like Chat Generative Pre-Trained
    Transformer (ChatGPT). It is all over the news. Everybody is
    chatting about it. It is a hot topic.
        The system that you are talking about was relatively simple
    and an older, automated system compared to what we are seeing
    right now. What are your thoughts on that fact and how it
    should inform our efforts to set Federal AI policy?
        Mr. Eppink. Yes. I guess for starters, black boxes are
    black boxes, no matter how big they get and no matter what is
    inside of them. Even though the Idaho system was just an Excel
    spreadsheet, it still ended up taking us a significant amount
    of time--I think it was maybe months, possibly a matter of
    years--to get all of the information on which it was built.
        Federal AI policy standards and enforcement that are
    governing use of automated systems and AI are not solving
    necessarily for the complexity of those systems. They are
    solving for the harms that they are causing.
        I do not know that we need new standards for each new
    technology. I think the same principles that we can apply to
    protect and prevent some of the things that we have had to
    litigate in Idaho would apply to more complex systems as well.
        Chairman Peters. Clearly, as I listen to your testimony,
    you believe that there is simply just not enough transparency.
    What would you recommend when it comes to holding these
    platforms more accountable?
        Mr. Eppink. What is critical is standards and enforcement
    that are specific to AI and automated decisionmaking systems,
    which we have had to enforce in Idaho through the litigation.
    We have basic American principles like due process and equal
    protection that are there. Where our courts struggle and where
    our agencies still have gaps as far as what they are overseeing
    is how to apply those in this new context to these automated
    systems. We know that the litigation in court, I think, is too
    unwieldly. Although we have done it in Idaho, it is not going
    to meet the proliferation of these systems.
        Each agency, for instance, with the Medicare program in
    Idaho, the Centers for Medicare and Medicaid Services (CMS)
    should be overseeing programs that are using automated systems,
    like Idaho, and making sure that they are complying with
    standards that are specific to those programs. We already have
    a lot of jumping-off points that can be used to develop those
    standards. They just need to be put in place and then enforced
    by these agencies.
        Chairman Peters. Thank you.
        Dr. Parker, I have two questions for you. First, some
    government uses of AI are clearly high risk, like when the
    Department of Homeland Security uses facial recognition
    technology. On the other hand, there is also some low-risk use
    of AI, like when the Forest Service classifies tree canopy
    coverage with machine learning tools.
        The first question. Should testing, auditing, and
    procurement requirements be different, depending on the type of
    system, and two, how should the Federal Government decide what
    is actually high risk and what is low risk?
        Dr. Parker. Thank you for the question, Mr. Chair. There
    are certainly many types of AI systems, and I think what is
    getting attention a lot in the press these days are some of the
    extreme cases. But we want to also encourage the use of AI in
    the mundane cases because they can improve services for the
    American people and they can improve efficiencies.
        NIST has come out recently, at the direction of Congress,
    with a NIST AI Risk Management Framework. I think evaluating
    the risks of each individual use case is important to have the
    right governance approach. We do not need onerous regulations
    and oversight of simple use cases that no one believes are
    going to harm anyone.
        Having that overarching policy, that for every use case of
    AI within the Federal Government those agencies step through
    the NIST AI Risk Management Framework, to determine what is the
    risk level. If it is low, then the steps that are needed in
    order to make sure it is used safely are much more minimized.
    If it is more consequential, then, of course, we do need to
    have much more oversight. Certainly GAO's Accountability
    Framework or the Blueprint for the AI Bill of Rights are
    designed to try to inform how to address some of those high-
    risk uses.
        Chairman Peters. Thank you, Dr. Parker. You mentioned the
    Government Accountability Office, so this question is for you,
    Mr. Ariga. In your testimony you mentioned how the GAO has
    created a toolkit to audit the AI system used by government,
    and that you are piloting that toolkit right now with one
    agency.
        My question for you is, can you tell us more about how the
    pilot is going, what roadblocks you may be facing, and at this
    time would it be feasible for all agencies to use the GAO
    Accountability Framework to audit their AI systems, and if not,
    why?
        Mr. Ariga. Thank you, Chairman Peters, for that question.
    GAO published our AI Accountability Framework back in the
    summer of 2021, and it is really a first-of-its-kind blueprint
    for agencies to consider as they navigate the AI development
    lifecycle. The basic premise is that if agencies can implement
    practices, entities like GAO can then come afterwards to
    identify and evaluate those, and point out any findings and
    recommendations there may be needed.
        Certainly GAO has a number of ongoing audits using the AI
    Accountability Framework, and we are also hearing that other
    oversight entities are also using the framework itself to
    conduct their AI evaluations.
        There are three challenges that particularly, I think,
    hamper the AI development within the Federal Government space.
    One is that while our framework looks at the AI development
    lifecycle, agencies can use more domain-specific guidance. For
    example, the ingredient list for transparency in medical
    diagnostics may look very different than facial recognition or
    even autonomous vehicles.
        We also need policies around the notion of privacy,
    transparency, and compliance. And then last, we certainly need
    a digital-ready workforce to implement those practices in a way
    that keeps humans in the loop.
        Chairman Peters. Great. Thank you.
        Ranking Member Paul, you are recognized for your questions.
        Senator Paul. When I first read 1984 I was concerned but I
    realized at the time we did not have the technology for 24/7
    surveillance and we did not have two-way television sets. There
    was not this ability to abuse our rights in such a systematic
    fashion. We do have that technology now, so it is of more
    concern. But I still think it is a mistake to concentrate on
    the technology and not the concentration of power. I, for one,
    do not fear AI at all if the Bill of Rights were protected. I
    think it really is a question of whether or not we would allow
    AI to invade our rights as protected by the Bill of Rights.
        Mr. Siegel, do you believe it is possible for the
    government to define and police disinformation without
    infringing on the First Amendment?
        Mr. Siegel. I think, Ranking Member, that if it was a
    strictly defined category of disinformation that applied
    specifically to foreign actors that had strict limits on its
    application, that it might indeed be possible but then in
    practice that is, that is not what its going to do.
        Senator Paul. I think that makes a good point. The Bill of
    Rights does not necessarily apply to every person living in
    Libya or Sudan or any other different country. We surveil them
    all the time. We collect all of the phone information. I think
    in one month we collected every phone call in Italy. I do not
    know why Italy, but we collected every phone call in Italy. The
    only way you could possibly get through that is with some kind
    of AI program. We have like thousands and thousands of hours of
    audio. The only way you could get through that is with help.
        But this is war we are talking about, when we are
    interacting with foreigners. When we are talking about us, we
    are supposed to have the Bill of Rights as protection.
        I guess I would make the point that I do not think
    disinformation for the U.S. citizen, I do not think it can be
    defined. I think it is in the eyes of the beholder. If you are
    willing to police information you run a great risk of
    infringing the First Amendment. I do not know how you do define
    disinformation.
        For example, in the Virality Project, which was from
    Twitter, but it also was Twitter working with the FBI, and the
    FBI paid Twitter for the information, they explicitly said that
    we need to take down things, even if they are true, if they
    might breed vaccine hesitancy. If someone did die from a
    vaccine and it is absolutely true, we are still going to take
    it down because the people are not smart enough to understand
    and have this information.
        Do you think for domestically, maybe part of the solution
    would be saying that we restrict this type of technology from
    being used to limit or hinder protected speech?
        Mr. Siegel. Yes, Ranking Member. I think that in the
    domestic context it is inherently if not unconstitutional then
    direct infringement on the Constitution, potentially, at least,
    and that it is also worth pointing out that from the origins of
    the modern U.S. counter-disinformation establishment in 2016,
    there are explicit references to the strategic difficulty in
    distinguishing between foreign and domestic actors.
        The origins of the Global Engagement Center (GEC), for
    instance, in 2016, there is already talk about how the
    internet, from the leaders of the GEC, about how the globalized
    nature of the internet makes it so that what are referred to as
    old-fashioned privacy laws are now a hindrance on the proper
    collection of what is considered to be relevant information in
    surveillance purposes.
        I think that in the domestic context not only is there an
    inherent difficulty in enforcing any standard of disinformation
    that is not inherently politicized, it also appears to be very
    difficult to make strict legal distinctions between foreign and
    domestic actors that are then enforced.
        Senator Paul. The simple way of narrowing it down is to put
    it in the context of the Bill of Rights, basically that if it
    is a right that is protective, AI should not be used in any way
    to define or limit that right. The forest canopy, I do not care
    of you use AI. Overclassification, we have 25 million records,
    and we want to run AI through it. My son writes the code for
    AI, so I am not against AI in any way, but it just needs to not
    infringe on speech.
        On the medical example, you have to have a human. Even with
    the overclassification problem, if you have an AI trolling
    through there to point out what could be declassified, still
    some human is going to have to look at it to declassify it at
    some point, but it helps to organize things.
        Really this is about protecting the Bill of Rights. But
    what disappoints me is in the current political atmosphere is
    there is not really so much a bipartisan concern for this. I
    have heard almost nothing from the other side on the idea that
    the FBI was going to Twitter and saying, ``Take down this
    information. We think this does not meet your policy,'' and
    Twitter is going, ``Well hell, it is a lot of work. Will you
    pay us?'' The FBI is saying, ``Yes, we will pay you to take
    down this information.'' They say, ``Is all of it
    disinformation, not true?'' ``Some of it is true. We just do
    not think it is helpful for society to read this. It is not
    helpful for them, even if it is true.''
        That should scare us all, on the right or the left, and yet
    the outrage seems to have been largely one-sided.
        For example, I have a bill, and it simply would say this:
    nobody in government can meet with, collude with, or work with
    anybody in media of any form to limit or restrict protected
    speech. The Constitution, the courts have defined protected
    speech. It would largely keep them out of this. Some people are
    like, ``Oh, people would say things are untrue.'' Yes, but
    unfortunately the First Amendment allows bad speech, allows
    people to say terrible things, and occasionally would allow
    people to say something. But most of the time there is actually
    a debate, with evidence on both sides, and that is what the
    news media is about, trying to figure out what the truth is. It
    is not like one source has all the truth.
        I think if we could get back to more discussing the Bill of
    Rights in the context of artificial intelligence I think we
    would have a better chance of getting to the solution. Sure,
    will there be some specific controls on artificial
    intelligence? Yes, but it is not so much that we should fear
    technology. We should fear the technology in the hands of
    people who would abuse our liberty.
        But thank you all for appearing.
        Chairman Peters. Thank you, Senator Paul.
        Senator Lankford, you are recognized for your questions.

                 OPENING STATEMENT OF SENATOR LANKFORD

        Senator Lankford. Mr. Chairman, thank you. Thank you all
    for being here and being in the conversation. Obviously, this
    is an ongoing conversation. I want to drill down on a couple of
    comments that a couple of you made and a couple of you have
    implied on this.
        Dr. Parker, you made the statement, ``responsible use of
    AI.'' Mr. Ho, you made the statement, ``responsible AI and AI
    innovation.''
        OK. Define for me what ``responsible use of AI'' is, and
    maybe that is the flip side of what irresponsible AI is.
        Dr. Parker. Thank you for the question, Senator. I think
    this is the million-dollar question, and this is the reason why
    I think guidance from OMB, for instance, as directed in the AI
    in Government Act and the Executive Order 13960 is so critical,
    because that process that agencies are expected to follow to
    ensure that their AI is used in a way that is upholding of our
    expectations for whatever responsible means is key. I think by
    defining the processes that agencies must abide by as they look
    at their use cases of AI, look at the risks of AI, that will
    inherently help us understand what is responsible.
        But if you look sort of theoretically at what responsible
    AI means, there are a number of principles that around the
    world we have converged on as those characteristics of AI that
    we agree fall into either what we call ``responsible'' or
    ``trustworthy'' AI. These are things like safe and effective.
    They are the way that the systems actually work is consistent
    with their intended use. We have accountability. There are a
    number of these kinds of principles that taken as a whole can
    be reflective of our sense of whether or not the AI system is
    trustworthy or whether or not it is responsible.
        To summarize, I think if we have AI systems that we agree,
    through a set of processes, that I think should be defined by
    OMB, that allows those AI systems to demonstrate those agreed-
    upon principles, then I think we would call that
    ``responsible'' use of AI and ``trustworthy'' AI.
        Senator Lankford. OK. Mr. Ho, do you want to take a stab at
    that?
        Mr. Ho. Sure. I agree with much of what Dr. Parker said. I
    think there actually is a fair bit of agreement when you look
    at various frameworks, the Executive Order 13960 on trustworthy
    AI within government, the Blueprint for an AI Bill of Rights,
    the NIST AI Risk Management Framework, and the GAO framework,
    that Taka Ariga mentioned. There have been attempts to try to
    actually look at the agreement, and there actually is fairly
    large agreement across these in terms of privacy protections,
    nondiscrimination, safe and effective forms of AI, and human
    awareness of how they are being used.
        I think the frontier of all of this is really how to take
    these principles and bring them into practice, and that is
    where having the requisite technical talent and leadership
    within government agencies is going to be so absolutely
    critical. Because we can all agree on principles in practice,
    but trying to actually drive them into operation I think is a
    really important frontier.
        Senator Lankford. Much of the AI conversation really boils
    around not just a responsible use but the data that is behind
    it. If the data is not good, then the whole system is going to
    be bad.
        Here is the fear that I hear from people is that if a wrong
    dataset ends up into the mix here and it affects you and your
    family, as you have dealt with in Idaho, and you have a false
    dataset or a false algorithm or something that has a glitch in
    it, you can be directly affected by that and you do not even
    know how to be able to reach into it.
        All these different AI researchers now are all trying to
    get more access to government data, No. 1, because it is
    perceived to be free, when actually the taxpayers paid for
    this, but they want to get mass amounts of data, they want mass
    amounts of faces, they want mass amounts of information. The
    Consumer Financial Protection Bureau (CFPB) just came out with
    a new rule for banks, for loans they want 80 different
    datapoints, and they want to make those publicly available.
        There is a huge amount of data that government is pulling
    and making it more and more available, where it is easier to
    connect the dots and to be able to identify individual people,
    where maybe that dataset does not identify that person, but it
    is not hard to get three different datasets, combine them
    together with their cellphone records that are publicly
    available for that data point, and to be able to identify this
    person and all of their habits, all of their locations,
    everything else.
        There is a concern on the availability of data that is out
    there and the continual push by every entity to say, ``We want
    our AI to be better. Our AI can be better, we want more data on
    every individual.'' Set that aside with responsible use of AI
    and with privacy, because right now privacy seems to be losing
    the battle, and so people can do more with AI because they
    could if they had more data.
        Where am I off?
        Mr. Ho. Senator, thank you for that exposition. I think
    privacy is absolutely paramount, and I think as the number of
    the panelists have noted, a national privacy legislation would
    be quite important here, where currently we have a system that
    is a kind of patchwork system.
        I think the other dimension that I would point out is that,
    I think going back to what Ranking Member Paul noted at the
    beginning in terms of the conversations in the 1970s, Congress
    made a choice to enact the 1974 Privacy Act that really only
    reached sort of the data that government agencies have, and
    really did not reach kind of the private sector.
        I think some of the places where we see the most acute
    concerns of hoovering up lots of data and identifying
    individuals is in the small number of technology companies that
    have scraped the entire World Wide Web and they are building
    models off this. That is why I think coupled with comprehensive
    privacy legislation, I think what is really needed is a kind of
    data strategy, and I think there are some really good
    blueprints for this in the National Secure Data Service that
    came out of the Evidence Act, that is trying to put in a series
    of kind of safeguards to really ensure that it is the right
    people with the right safeguards who have access to data. That
    is the same kind of blueprint that is being used for the
    National AI Research Resource, so that when folks have access
    to administrative data it is done in a secure and privacy-
    protecting way.
        Senator Lankford. Does anybody else want to make a comment
    on that?
        Mr. Eppink. Two other things I might add, Senator, on data.
    One is to recognize that, as I have talked about a little bit,
    the costs and the time necessary to analyze this data for
    someone who these systems are making decisions about is
    inaccessible. In the data, often, especially when you are
    talking about my clients who are people with developmental
    disabilities, is corrupted not only potentially by the creation
    of the data in the first place but by years and years of
    discrimination and other effects that have biased the data in
    the first place.
        Senator Lankford. Thank you, Mr. Chairman.
        Chairman Peters. Thank you.
        Senator Scott, you are recognized for your questions.

                   OPENING STATEMENT OF SENATOR SCOTT

        Senator Scott. First, thank you, Chairman Peters, for
    holding this hearing.
        Artificial intelligence surely has productive uses, but it
    can also present great threats, especially to our children.
    Today I am introducing my AI Shield for Kids (ASK) Act, to
    prevent children from accessing artificial intelligence
    features on social media sites without the consent of a parent
    or guardian.
        I have long been a supporter of doing more to keep our kids
    safe online. There is no doubt that we must do more to combat
    the emerging threats our children face each and every day on
    the Internet. Like probably some other people here, I have a
    bunch of grandkids, and I do not ever want to put them at risk.
        Mr. Ariga, AI poses significant risks to Americans,
    particularly vulnerable Americans such as children and youth.
    There are threats to privacy, user manipulation, and safety
    concerns. We know that AI regulation is lagging behind the
    speed of AI development and use. What guardrails are needed to
    protect vulnerable Americans from threats from intrusive AI,
    such as Snapchat's chatbot?
        Mr. Ariga. Thank you, Senator Scott, for that question. For
    us at GAO, we certainly believe in the ``trust but verify''
    part of that equation. We want to be able to assess implemented
    practices that agencies have adopted to make sure that they are
    in line with the internal control principles as well as in the
    areas of privacy protection and safeguards that you have
    mentioned.
        Within our AI Accountability Framework we have actually
    laid out specific practices in the areas of governance, data,
    performance, and continuous monitoring to make sure that the
    agencies themselves have infrastructure as well as evidence of
    those implementations, and in areas where we find potential
    recommendations and areas of improvement we will certainly
    issue findings in our report as well.
        Senator Scott. Snapchat admitted that their AI technology
    is experimental, so do you agree that it is alarming and
    problematic that Snapchat would force their users, which
    comprise almost 60 percent of American teens, to use their
    chatbot features unless they paid to disable it with a
    subscription service?
        It is hard to believe. If you do not want it, you have to
    pay to get it off, if you want to keep using Snapchat.
        Mr. Ariga. Yes, I will answer that. GAO's role is to
    provide rigorous oversight. Should agencies decide to use any
    AI technology, including Snapchat, we certainly stand by, ready
    to do the rigorous programmatic assessments of those programs,
    in line with what we have laid out in our Accountability
    Framework.
        Senator Scott. Do you think you ought to have to pay to get
    Snapchat off, The AI off your app that you want to use?
        Mr. Ariga. We will be interested in hearing the legal
    rationale and any other governance structures that arrive at
    that decision.
        Senator Scott. How about parents? Do you think parents and
    guardians have the right to protect their children and revoke
    consent without being charged a fee?
        Mr. Ariga. Certainly GAO has done a number of work around
    education, around childhood development, and so we would sort
    of take that similar approach at looking at programmatic
    implementation to see how that aligns with what we have laid
    out in the Accountability Framework.
        Senator Scott. Do you agree that you ought to get consent
    of parents for teenagers?
        Mr. Ariga. Again, I will go back to whether those legal
    rationales were done in a deliberately and sound way.
        Senator Scott. Do you have kids?
        Mr. Ariga. Yes, I do, two.
        Senator Scott. OK. Do you watch what they look at?
        Mr. Ariga. For sure. When my daughter looks at YouTube
    videos I certainly want to make sure that the content is
    appropriate for her age. As a parent I certainly share the same
    concerns that you do have. But from a GAO perspective, we try
    to be specific with our oversight role to say as agencies
    implement these capabilities there are specific sort of
    guardrails and expectations from internal controls that GAO
    will be looking at.
        Senator Scott. As a parent, do you think that you ought to
    have to pay to get AI off something that your teenager uses?
    Forget your job. Just as a parent, what do you think?
        Mr. Ariga. Fortunately, I do not have a teenage kid just
    yet. But eventually I think I will have to grapple with that
    reality, in addition to all the subscription fees that we have
    already paid for.
        Senator Scott. It appears that unelected administrative
    officials in DHS and CISA and others in this Administration
    have urged censorship on disinformation. It is frustrating when
    people say the border is secure and the laptop was not real,
    stuff like that.
        Mr. Siegel, as a writer, can you talk about the dangers of
    Big Government colluding with Big Tech and corporations to
    censor journalists like the New York Post on a story that was
    true?
        Mr. Siegel. Yes, Senator, thank you. I can address that. I
    think the dangers cannot be overstated. I think that kind of
    collusion between government and Big Tech and interference in
    open discourse in the political system is, strictly speaking,
    incompatible with the continued practice of democracy and self-
    government. I do not think that you can have free and fair
    elections when there is mass censorship occurring at scale,
    when there is collusion between various intelligence agencies,
    Federal agencies, not only Big Tech corporations but also other
    third-party, nonprofit actors who are essentially operating in
    a para-governmental role.
        I do not think that it is simply a question of censorship,
    though in a technical sense censorship is what is occurring and
    certainly that is bad enough. It seems to me to be a
    surreptitious form of government, that there is a form of
    governmental authority and control being exercised through
    these relationships, determining how Americans are conditioned
    to perceive various policies and acts of government, ranging
    from things related to public health and vaccines to foreign
    wars. That insofar as sovereignty has been secretly transferred
    from individual citizens to these new relationships of power,
    it seems to me incompatible with the traditional American
    system of democracy.
        Senator Scott. What do you think about the dangers and
    risks of the government potentially funding and moving toward
    algorithms that use AI technology to censor Americans online?
        Mr. Siegel. I think it is a related sense of risk, a
    related set of risks. I think that the greater risk, what we
    have not fully seen yet, is censorship that is effectively
    invisible because it uses AI to trap speech and narratives on
    the wire, as the phrase goes, meaning that rather than waiting
    for the New York Post to publish something, and then Twitter,
    Facebook, and other Silicon Valley companies operating under
    the direction of Federal Government agencies then censoring
    that information, potentially what we see in the future is AI
    being used to censor information before it is ever published.
    That could happen in forums where we have come to expect mass
    censorship and which we view as public forums like on Facebook
    or on Twitter, for instance. But it could also happen on what
    you might think of as the back end.
        For instance, Google was censoring Google Docs during the
    pandemic. There was a white paper on hydroxychloroquine that
    was published to Google Docs, and I think most people's
    understanding of Google Docs is that it is a kind of semi-
    private document that Google has given to you as one of its
    suite of services. But that illusion of ownership or control is
    just that--it is an illusion. This paper, white paper, whatever
    one thinks of its contents, was deleted by Google without
    explanation, without reference to any formal policy violation.
        It is those kinds of invisible censoring acts occurring at
    scale that I think AI could drive, and it would be an even more
    significant threat than what we have already seen.
        Senator Scott. Thank you. Thank you, Chairman.
        Chairman Peters. Thank you, Senator Scott.
        Senator Hassan, you are recognized for your questions.

                  OPENING STATEMENT OF SENATOR HASSAN

        Senator Hassan. Thank you very much, Mr. Chair, and I want
    to thank you and the Ranking Member for holding this hearing,
    and I really want to thank the witnesses for being here today.
    Thank you for sharing your expertise and perspectives with us.
        I want to start with a question to you, Dr. Parker.
    Congress created the National AI Initiative Office to improve
    efficiency and help Federal and local governments, researchers,
    business leaders, and other stakeholders collaborate on AI
    issues. You were the first National AI Director, but that
    position has remained vacant since you left the post in August.
        As the former Director, why is it important that we fill
    this position?
        Dr. Parker. Thank you, Senator, for that question. The
    National AI Initiative Act of 2020 set up three very important
    goals for our nation about us leading the world in AI research
    and development (R&D), about making sure that we also lead in
    the development of trustworthy AI and both the development and
    use of trustworthy AI in both the public and private sectors,
    and to make sure that we are educating and training our
    workforce to participate in these AI activities.
        It also put in charge of these activities the National AI
    Initiative Office, and that is in addition to a coordination
    role among all the Federal agencies and what they are doing in
    the AI space.
        Given the magnitude of the importance of the National AI
    Initiative, as set forth by Congress, I think it is imperative
    that we have leadership in the White House that is overseeing
    these activities, that is pushing forth the innovation and the
    research that we need to address many of the kinds of concerns
    that have been raised in this panel so far, to make sure we are
    training and educating our workforce and leading new
    initiatives across the government that could help advance
    these, and the governance issues that we are addressing today.
        That leadership vacuum I think has contributed to a number
    of challenges that we have across the board, in terms of being
    able to implement these good policies that are in place.
        Senator Hassan. Thank you very much for that.
        To Mr. Ariga, AI researchers have highlighted some of the
    potential public safety risks posed by AI systems. These safety
    concerns include AI systems providing dangerous information to
    bad actors or potentially acting in unpredictable ways that run
    counter to the intent of designers. Increasing the safety and
    predictability of AI systems requires more technical research
    into the methods used to create these systems. What can the
    Federal Government do to support or coordinate research that
    would help improve the safety of AI systems?
        Mr. Ariga. Thank you, Senator Hassan. In our AI
    Accountability Framework we laid out specific governance
    practices where agencies can adopt to really consider, for
    example, is AI even necessary in this particular use case? In
    fact, if it is, what are some of the organizational structures
    that are in place to assess the legality, the compliance
    factor, as well as driving some of these inherently
    governmental functions?
        We go back to our framework itself that lays out not only
    governance but looking at data performance, as well as the
    important topic of continuous monitoring when it comes to AI.
        Senator Hassan. Thank you. Another question for Dr. Parker.
    Congress created the National Artificial Intelligence Strategy,
    as you noted, to establish goals, priorities, and metrics for
    guiding and evaluating interagency work on AI. That strategy
    focuses on things like AI research and investments in workforce
    development. However, the strategy does not currently require a
    strategic level focus on safeguards to prevent AI from being
    used in a manner that harms our country or society.
        Can you speak to how a focus on AI safeguards could be
    incorporated into the National AI Strategy?
        Dr. Parker. Yes. Thank you, Senator. I think it is true. If
    you look at, say, the role of the National AI Initiative
    Office, it is to oversee the research and the education and the
    coordination, but it does not provide a role for that
    governance. We need an approach to be able to govern that
    responsible use of AI.
        I think one thing that could be done is to have kind of a
    two-part approach. One is to have Chief AI Officers at every
    agency that are responsible for these kinds of activities
    within each individual agency. This has been a challenge
    because even in the Executive Order 13960, that requires
    agencies to identify a responsible AI official, that has not
    happened well. We do not have a single point of contact or a
    single responsible person at the agencies that oversee these
    activities.
        But agencies all have different missions, and so in order
    to coordinate in a consistent way across all of the Federal
    agencies I think the creation of something like a Chief AI
    Officer's Council, that is led by OMB and OSTP's National AI
    Initiative Office, perhaps with representation from the General
    Service Administration (GSA's) Center of Excellence (COE) in AI
    as well as the Community of Practice would provide the
    expertise across the Federal agencies to coordinate these
    processes and provide the leadership for the government as a
    whole.
        Senator Hassan. I think that makes a lot of sense, and,
    when you think about emerging technologies generally we tend to
    focus on the potential of the technology without thinking about
    the necessary safeguards, in my view, early enough. I think a
    lot of what you have heard around the dais this morning is
    concerns about the safety issues and the way that AI can impact
    our democracy, but we need to be thoughtful about how we can
    actually address those issues in a way that is consistent with
    our values. I appreciate your answer.
        I do have another question for you, Dr. Parker, on deep
    fakes, which are obviously images and videos that are generated
    artificially, and they are becoming increasingly realistic.
        Last year, malicious actors deployed a deep fake video of
    Ukrainian President Zelensky telling Ukrainian soldiers to lay
    down their arms and surrender to Russia, for example. As
    artificial intelligence advances, deep fakes like the Zelensky
    one will become harder to identify and debunk, and I am
    concerned that in the hands of our adversaries, deep fakes pose
    a really significant threat.
        How do you assess the Federal Government's current efforts
    to identify and debunk deep fakes? How can the Federal
    Government prepare for a future with extremely realistic deep
    fakes?
        Dr. Parker. Thank you, Senator. I am a technologist, and so
    I think often of these challenges from a research perspective
    and what we can do in terms of coming up with new approaches
    that help us address these kinds of challenges. There are some
    activities in the research space to do things like
    watermarking, that can allow you to determine how a particular
    piece of data or an image or a video, where it came from, what
    we call the provenance of it, what its history is.
        Those kinds of approaches, if we could watermark these
    kinds of images and content in a way that allows us to trace
    back its origins and where it came from, and is it real or is
    it not real, that is a step forward to giving us the technical
    ability to address these kinds of challenges.
        On top of that, of course, are the governance approaches,
    and frankly, I did not do a lot of work myself in government
    work and the governance of deep fakes. But I think the
    technical approaches that I mentioned will help, and so
    certainly an increased attention to those kinds of technologies
    is helpful.
        Senator Hassan. Thank you, and I am over time. I will
    follow up with one of the questions I think we will face, Mr.
    Chair, is how does the government work with the private sector
    and academic to try to make sure that we are harnessing various
    ideas and approaches here. Thank you very much.
        Chairman Peters. Thank you, Senator Hassan, and actually,
    that topic is going to be a future hearing, because it is
    incredibly important. We will look forward to discussing it at
    length.
        Senator Rosen, you are recognized for your questions.

                   OPENING STATEMENT OF SENATOR ROSEN

        Senator Rosen. Thank you, Chairman Peters. I really
    appreciate you holding this hearing today, and thank you to all
    the witnesses, for all you do, for your work and your
    thoughtfulness in this really important area.
        Of course, we are talking about standards, and all of us
    are worried about technology moves faster than we can
    oftentimes even adapt to it and figure out what we need to do.
    Standards are really important. We know that China has explicit
    plans to become a standards-issuing country, and part of its
    push to increase global influence, it coordinates national
    standards work across government and industry. China's
    strategy, they involve targeting emerging technologies like
    quantum computing, big data, 5G, artificial intelligence, where
    the global rules really have yet to be defined.
        In order for the United States to remain a leader in AI and
    maintain a national security edge, our response must be one of
    leadership, coordination, and above all, cooperation, and this
    means working, like Senator Hassan said, with the private
    sector and academia, investing in R&D for emerging
    technologies, coordinating with relevant agencies, and engaging
    with international standards-setting bodies.
        Mr. Ho, can you describe the importance and impact of U.S.
    participation in these international standards-setting bodies
    for the development of emerging technologies, including AI?
        Mr. Ho. Thank you for that question, Senator Rosen. I think
    you may have been one to introduce legislation that actually
    fosters international cooperation, and I think that is exactly
    the kind of effort that is required right now in this context
    of geopolitical competition, where if it is possible to have
    international cooperation schemes with like-minded countries,
    there is a way really to address this current question of the
    concentration of who really builds, owns, and guides these
    kinds of AI systems.
        One proposal that is very much in line with what you
    proposed earlier is the proposal for the Multilateral AI
    Research Institute, to enable like-minded countries to
    collaborate together, to engage in this kind of standards-
    setting. I think that is an absolutely critical potential path
    forward for the future.
        Senator Rosen. Thank you for bringing that up because I do
    believe by doing nothing we are actually doing something. That
    leads me to my next question, to Dr. Parker, and again, to you,
    Mr. Ho.
        Earlier this year, the National Institute of Standards and
    Technology did release an AI Management Framework, with the
    goal of improving trustworthiness of artificial intelligence,
    like we are talking about deep fakes and others. About three
    months later, the White House Office of Science and Technology
    Policy issued its Blueprint for an AI Bill of Rights.
        How should the private sector view these two bills? Are
    they complementary? Do we need to merge something into one?
    What are both of your opinions on this.
        Dr. Parker. Thank you for that question, Senator. The NIST
    AI Risk Management Framework is a framework that applies, in my
    opinion, to any use case of AI. It gives you a standard
    approach to be able to consider any given use case of AI, and
    step through a number of areas as it relates to identifying
    risk and governing and managing them, and so forth.
        The answer there may be that that particular use case of AI
    is low risk, so the additional steps that might be needed to
    govern it might be a few, or it could be much more substantial.
        The Blueprint for the AI Bill of Rights that the White
    House OSTP issued is coming at the challenge from a very
    specific category of applications of AI, and these are
    applications of AI that may harm individuals or community
    groups or society in terms of your civil rights and civil
    liberty and privacy, your access to resources, and that type of
    use case.
        After applying the NIST AI Risk Management Framework, high-
    consequence risks were identified, and particularly that affect
    individuals or, again, communities or society, then the
    Blueprint for the AI Bill of Rights would be a way to think
    through what are the rights of an individual and what are those
    issues that need to be addressed.
        Senator Rosen. Those are complementary. Thank you. Mr. Ho.
        Mr. Ho. Yes, I think it is a really important question.
    There are a lot of commonalities in terms of the principles
    that the NIST AI Risk Management Framework, the Blueprint for
    an AI Bill of Rights, and Executive Order 13960 are trying to
    get at.
        What I have seen in a number of agencies is a real struggle
    of how to actually bring that into practice when agencies are
    thinking about piloting, evaluating, and implementing these
    kinds of AI use cases. That is why I think what is really
    critical, and what I highlighted in my opening remarks, is to
    build pathways for technical talent into the public sector. It
    will not be possible to really do the kind of red-teaming,
    evaluation of these kinds of use cases unless we build on
    existing short-term programs like the Presidential Innovation
    Fellows (PIF), the GSA, things like the Intergovernment
    Personnel Act (IPA) mechanism, but also think about long-term
    pathways, things like the U.S. Digital Service Academy, and why
    it is so important that OPM actually create the AI hiring line
    that was due as of July of last year.
        Senator Rosen. You did not really know my next question,
    did you, because it really is on the workforce challenges, so
    you set me up just perfectly there. Our existing cyber
    workforce shortages, we know at Federal agencies they have a
    really significant impact on our national security, so the
    private sector trying to hire for AI, for cybersecurity,
    everything in the technology space. There is really this huge
    gap between talent and the jobs that we have to fill, so we
    have to continue to invest in our cyber workforce.
        I am going to ask both of you again. Dr. Parker, how do you
    think we can use AI in the short term to overcome cybersecurity
    skills shortages across Federal agencies, knowing that I
    believe AI potentiates what humans can do and may help us do
    things faster, but in the end humans need to make those
    decisions. But what do you think we can do while we are
    building the pipeline?
        Dr. Parker. I do think that there are some uses of AI, some
    applications of AI that are increasing productivity of
    individuals. That is true for many different kinds of areas.
    You asked about cybersecurity, in particular, or just the cyber
    workforce in general. I think being able to use AI, again, in
    ways that are somewhat mundane, but there are ways that we can
    manage a lot of paperwork and be able to identify ways that we
    can more efficiently address the needs of the American
    consumer.
        I do think it is challenging at the moment to say that we
    can use AI as a substitute for people. I think AI is not ready
    for that. I think AI is very much more a collaborative tool,
    and as a collaborative tool it can help, again, people to work
    more efficiently. At the same time, we desperately need to work
    on getting more expertise into government.
        One quick way of doing that, I think, is to leverage these
    programs like the Intergovernmental Personnel Act and the
    Presidential Innovation Fellows Program to get people from
    industry and from academia into government. I think that is a
    very quick way to leverage those programs more, to get more
    expertise in government.
        Senator Rosen. Thank you. I am over my time, so do you want
    me to let him finish or take it for the record later, Mr.
    Chairman.
        Chairman Peters. Be quick.
        Mr. Ho. I will be quick. One estimate has it that we need
    40,000 positions in the public sector for cybersecurity. It is
    absolutely critical to figure out the pathways of bringing
    people in.
        I think it is not just a matter of salary scales. As I
    mentioned in my opening remarks, the National Security
    Commission on AI really highlighted that what is really needed
    is also providing opportunities for technical talent to perform
    meaningful work within government.
        The last thing that I will just say quickly, as to why
    really the way I tend to think about it is augmenting the
    existing Federal workforce rather than displacing them, is that
    you are always going to ultimately need a human in charge.
        I will give you one example going back to 1983, when there
    was an automated missile detection system that the Union of
    Soviet Socialist Republics (USSR) was using, that indicated
    that there were multiple missiles being fired. There was one
    individual by the name of Petrov who went against strategic
    operating protocol because he had a hunch that the system was
    malfunctioning. He is often said to be the person who actually
    saved us from nuclear war.
        We have to have humans in charge to understand the
    limitations of these kinds of systems, who know when humans
    should override them, in order to really work effectively and
    safely with these kinds of systems.
        Senator Rosen. Thank you. I could not agree more.
        Chairman Peters. Thank you, Senator Rosen.
        Senator Padilla, you are recognized for your questions.

                  OPENING STATEMENT OF SENATOR PADILLA

        Senator Padilla. Thank you, Mr. Chair. I wanted to thank
    you also for your flexibility. I am back and forth with the
    Judiciary subcommittee on AI this morning as well.
        Artificial intelligence is already transforming how
    government agencies serve the public. Federal agencies are
    leveraging AI in a number of important ways, including to
    support disaster response and emergency management efforts, to
    detect financial fraud and identity theft, to offer chatbots
    and virtual assistants that enhance customer service and
    engagement, as well as for environmental monitoring and
    conservation.
        I lay this out because a lot of times we are trying to have
    these conversations about AI, the potential, some risks, and
    things to keep in mind, as if it is a far-off-into-the-future
    dynamic. No, this is a here-and-now conversation.
        But clearly there are risks that we will need to address,
    especially the sensitive context of providing government
    services. Automated decisionmaking systems and tools risk
    exacerbating the many existing inequities in our society, as
    some of the testimony today reflects. Again, Mr. Chairman,
    thank you for calling this hearing. I look forward to hearing
    from our panel today on how we can ensure that fostering
    trustworthy, equitable, and accountable applications of AI in
    government can be achieved.
        Now in reviewing the published inventory of AI use across
    the Federal Government--again, today, not into the future--I
    was pleasantly surprised to see that many agencies are building
    AI tools in-house. Some argue that it is more cost effective
    for our government to simply purchase AI products developed by
    the private sector, whether it is off the shelf or customized.
    However, many of the testimonies that we have heard today
    explicitly mentioned that government technologists and in-house
    tools are important to ensuring that they comply with the
    relevant regulations and have the focus of furthering agencies'
    mission, not always achieved when you contract out.
        Mr. Eppink, first question. In your testimony you
    highlighted some of the tensions that arise when government
    relies on proprietary private sector tools that are not always
    available for public scrutiny. What are some of the factors
    that should go into agency decisions to build a tool internally
    as opposed to procuring it externally?
        Mr. Eppink. Thank you, Senator, for the question, and you
    are absolutely right. This is definitely a here-and-now
    problem, and we do have these frameworks that have been
    discussed today, but what we do not have, at least that I have
    observed, is the on-the-ground enforcement and policing of
    those, and that is especially true when it comes to these in-
    house versus proprietary systems.
        This should be an easy question, I think. We cannot allow
    proprietary interests--when we are talking about government
    making decisions about individuals and their families--to hold
    due process rights hostage. To the extent that a government
    agency or a State-funded agency needs to use, or wants to use
    automated decisionmaking if they have gone through the process,
    a transparent process of deciding that that is appropriate in
    the first place, if there is going to be proprietary or private
    interest providing any of that, the price of admission is going
    to have to honor Americans' due process rights, equal
    protection rights, which would mean the transparency of those
    proprietary systems, so that my clients, for instance, in
    Idaho, can access the information about the data, the methods,
    and the processes involved so they can evaluate whether they
    need to challenge those government decisions, and challenge
    them and appeal them if they have to.
        Senator Padilla. Thank you. For the follow-up question I
    invite Dr. Parker and Professor Ho to chime in. What are some
    of the short-term steps Congress can take to help agencies hire
    and retain technical talent in this area? We heard from Senator
    Rosen about the field, in general, I think more in the private
    sector the need for some of the workforce challenges in this
    space. But on the government side, in particular.
        Dr. Parker. Thank you for that question. I think there are
    a number of barriers right now to having that type of expertise
    in government. One of the barriers, I think, is a salary
    barrier, and an understanding of the kinds of skills and
    knowledge that are needed in order to fill a particular AI
    role. I think if the occupational series that OPM is working on
    were developed, it would help us to identify what those skills
    and roles and knowledge are that are needed for certain jobs in
    AI in the Federal Government, and that would give us more
    ability to reach out to people that have those kinds of skills
    and to train to those skills through things like boot camps.
        A few years ago there was a boot camp in cybersecurity that
    brought in people from across the Federal Government who were
    interested in learning cybersecurity skills but did not yet
    have them. The Chief Information Officers (CIOs) got together
    and trained these people, and they now have those additional
    cybersecurity skills. We could do something similar in AI.
        The challenge is always how to scale it. Congress could
    fund these kinds of boot camps so that we could use the current
    workforce that we have but to provide those new skills and
    knowledge that is needed to participate in the AI space.
        Senator Padilla. Professor Ho, anything unique to add,
    because I have an additional question on a different topic for
    you as well.
        Mr. Ho. I will just say, quickly, as I see on this side of
    the coast, Senator, I will say quickly the other part is to
    build on Science, technology, engineering, and mathematics
    (STEM) education. I think for the longest period of time the
    United States has just been a magnet for top scientific and
    technical talent. But increasingly there are international
    students that are choosing to leave the country. The country of
    Canada, for instance, has had very specialized programs to
    actually attract top AI talent into the country, and that would
    be another mechanism really to ensure that we maintain U.S.
    leadership in AI.
        Senator Padilla. You frame it as many graduate students
    choosing to leave the country. In too many instances there is
    no choice, given our immigration system, the need for
    modernization, but that may be a topic for another day.
        Professor Ho, I mentioned another topic I wanted to make
    sure to ask a question on. In the paper that co-authored on the
    use of artificial intelligence in Federal administrative
    agencies, you found that law enforcement applications were the
    most common use case for Federal agencies that adopted AI
    systems.
        As you talk about building trust and ensuring
    accountability for automated decisionmaking, law enforcement
    activity is often the area in which the public has the least
    amount of insight, let alone oversight, yet it is also the area
    where government decisionmaking, including tools used to guide
    that decisionmaking, have tremendous consequences for the
    public, particularly for historically marginalized communities.
        Professor Ho, can you speak to the unique challenges of
    guarding against bias and ensuring accountability and equity in
    the use of AI by law enforcement?
        Mr. Ho. Thank you, Senator, for that question, and thank
    you for noting the report that we conducted a number of years
    ago. I should clarify that in that report we looked largely at
    the use of AI by civil agencies, and one of the challenges has
    actually been exactly to get transparency within the criminal
    justice system. That is reflected, as well, in some of the
    exemptions under, for instance, the AI Bill of Rights or the
    scope of requirements to file AI use case inventories. That is
    why I think these AI use case inventories are such a kind of
    critical tool of transparency. You cannot manage what you
    cannot measure, and so I think AI use case inventories are an
    important first step in that regard.
        Let me loop back, though, to the earlier question that you
    had, just in terms of accountability, and give you one example
    of the sort of enforcement context that I think is very telling
    that connects this to the necessity to have human talent within
    government. Within the Securities and Exchange Commission (SEC)
    there was an internal team that built out a series of very
    innovative ways to scan filings, to look at the risk, for
    instance, of insider trading based on what folks had filed to
    the SEC, using natural language processing.
        But what was very important in that use case was that it
    was internally developed first, and it was the interaction
    between the technical engineers and the line-level prosecutors
    that really ensured accountability. The line-level prosecutors
    within the SEC said, ``I am not persuaded by your risk score.
    You need to explain to me why this system is actually
    identifying this case as something that I should prosecute,
    because ultimately I need to bring this in front of a judge.''
    That is exactly the reason why technical talent and the ability
    of technical talent to work with the domain experts is going to
    be so critical to have these kinds of forms of internal
    accountability for AI systems.
        Senator Padilla. Thank you very much, and Mr. Chair, if I
    could just add one last note, not another question but just one
    last note. Tapping into my prior experience as Secretary of
    State of California, where we introduced the first chatbot in
    California State government to assist people navigating our
    website, also automating how business owners and entrepreneurs
    could file their necessary paperwork with the State of
    California, there is, at times, a personnel concern that
    through additional automation and efficiency that we do not
    need as many workers, and therefore it is a mechanism toward
    layoffs and staff reductions.
        What we were able to do instead was actually free up
    people's valuable time from, ``pushing paper'' to improve
    customer service and dedicate that experienced frontline
    personnel to some of the more complex questions or
    troubleshooting that a lot of either individuals or customers
    of government sometimes have frustrations with, long wait
    times, et cetera. There can indeed be that win-win.
        Thank you, Mr. Chair.
        Chairman Peters. Thank you, Senator Padilla.
        Senator Ossoff, you are recognized for your questions.

                  OPENING STATEMENT OF SENATOR OSSOFF

        Senator Ossoff. Thank you, Mr. Chairman, and thank you to
    our panelists for joining us today.
        Some of these questions I think will get at implementation
    within government and some will also touch upon how we think
    about potential proposals for broader regulation of the
    technology, so please bear with me as we move through the
    discussion.
        First is about definitions, and maybe Dr. Parker, I could
    start with you, and I would also like to hear from Professor
    Ho. But as these technologies become more ubiquitous and
    modular and they are incorporated in software suites, and they
    are plugged in as tools for various purposes throughout an IT
    infrastructure, how, both in terms of administering within
    government, their deployment, but also thinking about broader
    regulation do we fundamentally define what it is that we are
    regulating? As concisely as you can, how would you define the
    scope of the technologies that are the subject of our interests
    and require additional scrutiny?
        Dr. Parker. Certainly the definition is something that
    people do not agree on, in general. I like to focus on use
    cases and how the use of a technology is important in impacting
    the particular application domain.
        I look at it in terms of systems that are typically data
    driven, they often learn over time and change their behavior
    over time, and they are often doing tasks that we frequently
    have attributed to require human intelligence in the past. That
    is my succinct definition.
        Senator Ossoff. OK. Thank you, Dr. Parker. Professor Ho,
    again, imagine you are legislative counsel and you are drafting
    legislative text, and your purpose is to define the technology
    subject to certain regulations. What text would you propose?
        Mr. Ho. I very much agree with Dr. Parker that the focus
    should be on use cases. I think a lot of regulations refer back
    to the National Defense Authorization Act (NDAA) definition,
    which is a relatively expansive one. One way to handle this, I
    actually think it would be to have further guidance and
    clarification coming out of the relevant offices that are
    working with agencies. For instance, the inconsistency in how
    AI use case inventories have been handled steps exactly from
    your question.
        Senator Ossoff. Is it about use case or is it about
    capability? The use case is going to be almost universal, I
    think, within a couple of years. Is it the purpose for which it
    is being used that defines whether it constitutes the regulated
    technology, if we are thinking about regulation, or is it the
    capability of the technology as the qualities of the software?
        Mr. Ho. I think, definitionally, we can go with the
    capabilities of the software, and that is very much, I think, I
    would agree with Dr. Parker that the kind of focus typically
    has been on machine learning systems that are able to learn and
    predict in the way that really simulates what humans could do.
        But I think when it comes to the actual regulation, which I
    think you are also trying to get it, it is really important to
    look at the particular use cases to identify what kind of risks
    are being posed.
        Senator Ossoff. All right. Let us think about some of the
    constitutional and other questions that may arise. Mr. Eppink,
    from your standpoint, thinking about, for example, evidentiary
    predicate that justifies certain police actions or can be used
    to secure certain court orders. One of the things that I have
    been grappling with is given the massive datasets that are
    available in open source or that can be purchased by a state
    actor, the capacity for predictive behavioral modeling is
    potentially very significant. Perhaps with a high degree of
    integrity some of this technology will be able to assign
    probabilities with respect to future conduct by individuals.
    The risk here, I think, is that prosecutors or law enforcement
    agencies may use such predictive modeling in order to justify
    forms of surveillance or to seek warrants or to take other
    action.
        How do you think about that risk and how should Congress
    think about that risk?
        Mr. Eppink. Thank you, Senator. Yes, especially based on
    what we have heard today, we have, I think, at best, principles
    to start to think about how to build these systems in a safe
    way, in a democratic way, but I do not believe they are being
    built that way right now. Especially when we are talking about
    law enforcement and the risk of life and liberty, the
    technology may be developing but the governance of that
    technology is not yet there to be condoning use of AI in those
    contexts. I am not even sure, based on what we have seen in
    Idaho in the Medicaid context of comparatively very rudimentary
    automated system, that we are there yet, and I think the
    necessity of litigation there corroborates that.
        We have to go beyond these jumping-off points that we have
    been discussing today, create clear governance, and include the
    people who these systems will be making decisions about in the
    process of selecting whether there will be automated
    decisionmaking in the first place and how those things will be
    crafted to ensure that the systems are built fairly and used
    fairly.
        Senator Ossoff. Dr. Parker, how do you think about the due
    process concerns, and those could be both in a criminal context
    or in a more seemingly mundane administrative context, like
    eligibility for certain forms of aid?
        Dr. Parker. I think this is a complex question, Senator,
    and thank you for that.
        Senator Ossoff. You have one minute and nine seconds.
        Dr. Parker. I am not going to answer it all. I am going to
    suggest that one way to move forward is for the Subcommittee on
    AI in Law Enforcement that was directed by Congress in the
    National AI Initiative Act, to actually be established. This is
    something that is a subcommittee of the National AI Advisory
    Committee, and that would be experts from across the different
    sectors of interest, whether it be private sector or----
        Senator Ossoff. OK. So more study needed.
        Dr. Parker [continuing]. A group of experts that can enable
    us to understand this more deeply.
        Senator Ossoff. OK. Big subject, seven minutes.
        My final question for you, Dr. Parker--and you have
    probably thought about this a lot, now and in your past roles--
    in government there is a lot of focus on insider threats,
    whether in an intelligence context or otherwise. When we are
    thinking about autonomous actors, or actors who have a measure
    of autonomy, within public agencies, who are not humans, how do
    we think about the risk of cooptation, manipulation,
    exploitation--there is cybersecurity aspect here. There is a
    software design aspect here--that these tools themselves could
    pose certain insider threats for unauthorized disclosure or for
    using their network accesses to enable penetration of
    government systems, or otherwise.
        Dr. Parker. I think there is a question of what could be
    and what is true today. I do not work in the national security
    space myself, but I think what we can do with AI systems right
    now are there are technologies, if you are thinking about a
    human insider threat, there are technologies that can actually
    track behaviors and determine whether or not people are doing
    what they should be doing in the intelligence system space. I
    am talking about inside the trusted people. There are those
    kinds of technologies that can help us protect against the
    human insider threat.
        But then there is also the bigger question of down the road
    if these more general AI systems have the capability to dig
    into our systems and what we do about that. That is not
    something that I think is the here and now. I think it is
    something that we need to think ahead on. But I do not believe
    those systems exist today.
        Senator Ossoff. Mr. Chairman, could I ask one more
    question? I am over time.
        OK, please, as succinctly as you can, Dr. Parker, and then
    Mr. Eppink, if there were three State actions, things that
    governments do, where, referencing what Professor Ho said
    earlier, we not only must ensure that humans are in the loop,
    but let us say we wanted to take a provisional decision that at
    this time no such action should be permitted to be even
    influenced by this kind of technology. Like for example,
    decisions about when to use lethal force, decisions about when
    to conduct surveillance.
        Are there certain governmental functions that given the
    level of risk right now you would nominate to rule out as being
    supplemented or guided or supported by these technologies, or
    are there not?
        Dr. Parker. The launching of nuclear weapons, for instance.
    I think DOD is overseeing a number of ethical uses of AI, but
    there are some cases like that, that I think strategically
    cannot be allowed to happen. That would be my No. 1 on the
    list.
        Senator Ossoff. Mr. Eppink.
        Mr. Eppink. Yes, I think we can look to the Constitution.
    We can look to life, liberty, property, privacy. To the extent
    that we have systems that are involved in making decisions on
    those things that affect individuals and families, we have to
    ensure that there is the transparency, the inclusion, the
    reliability, the independent auditing and testing of those
    programs before they should be deployed in government uses.
        I think we can get there, in some instances, but we are not
    there now, and especially when you were talking about making
    decisions about use of lethal force or other decisions that
    could take a life or threaten a life. I think there is
    governance that is not yet in place to ensure those systems are
    fair.
        Senator Ossoff. Thank you. Thank you, Mr. Chairman.
        Chairman Peters. Thank you, Senator Ossoff.
        We are ready to wrap up a great hearing. We have covered an
    awful lot of ground, a big topic. I would like to wrap up these
    kinds of hearings with just asking folks to kind of focus one
    of the issues.
        I am going to be asking everybody on the panel--and I am
    going to start with you, Mr. Siegel, and then we will work down
    the panel--so in terms of AI policy going forward, what would
    you say, from a legislative standpoint, because we are
    legislators here, in Congress, in terms of legislating, what
    would be the No. 1 item that we should prioritize in terms of
    thinking about future legislation?
        I am going to start with you, Mr. Siegel. All of you have a
    lot of different issues that you are working with, but No. 1,
    for legislating. There are other things that we could be doing,
    regulations and other kinds of policies, or norms, et cetera,
    but from a legislative standpoint is there something that
    really stands out to each of you?
        Mr. Siegel.
        Mr. Siegel. Understood, Mr. Chairman. Transparency would be
    the No. 1 issue from a legislative point of view, enforcing
    transparency in the use of AI. I think that if you were to
    focus legislatively on transparency that would take care of a
    host of attendant issues such as collusion between the
    government and corporate sector, privacy issues, even
    potentially pointing the way toward some kind of private data
    ownership so that the uses of people's data was something that
    if they were not at least initially financially staked into,
    they could at least have some visibility on.
        Transparency, I think, is where to begin, and from there
    that would lead into other related matters.
        Chairman Peters. Thank you, Mr. Siegel. Mr. Ho.
        Mr. Ho. Chairman, a number of months ago, Eric Schmidt was
    asked about how Congress had implemented the recommendations
    from the National Security Commission on AI, and he was
    generally quite favorable. But there was one thing he singled
    out, which is getting technical talent into the Federal
    workforce, which is the predicate for, I think, addressing a
    range of these issues that we have talked about today.
        Take procurement. I think the AI Training Act is fantastic.
    But what I have seen at a number of agencies is that
    procurement officials say, ``It is the business unit within the
    agency that has to make this decision,'' and the business unit
    says, ``It is really up to the procurement official.'' I think
    what we really need is the kind of blended expertise that
    brings domain expertise and technical talent together to really
    be able to protect American values.
        Chairman Peters. Thank you. Dr. Parker.
        Dr. Parker. Thank you, Mr. Chairman. I would say that we
    are suffering right now from a lack of leadership and a lack of
    prioritization on these topics. One, I think, quick way,
    legislatively, that could be done to address this is to appoint
    those Chief AI Officers at each agency, where they are given
    the responsibility and the resources to oversee the uses of AI
    and to develop strategies for their use of AI within their
    agencies, with accountability for delivering those and updating
    them regularly.
        To establish a coordination body, like a Chief AI Officers
    Council, that is responsible for coordinating these activities
    across all the Federal Government, with an intent of
    prioritizing this activity across the Federal Government,
    providing that leadership as well. Then they can also work on
    helping with the workforce issues, I believe, within their
    agencies, by identifying what the needs are and putting those
    priorities on getting that workforce into the Federal
    Government.
        Chairman Peters. Thank you. Mr. Ariga.
        Mr. Ariga. Thank you, Chairman. My No. 1 priority, and you
    might indulge me in the hyphenated response, one is on
    disclosure where discretionary decisionmaking is being
    impacted. The use of it, the process, and any redress. But
    fundamentally it is the digital-ready workforce that will make
    such disclosure effective. I will echo with Dr. Ho's
    recommendation in terms of developing a Federal digital-ready
    workforce.
        Chairman Peters. Thank you. Mr. Eppink.
        Mr. Eppink. Thank you, Chairman. The experts on these
    systems are the people that the systems make decisions about. I
    worked on this litigation in Idaho for 12 years now, almost,
    and I have worked with agency officials, I have communicated
    with Federal overseers, I have communicated with the courts.
    But it is time and time again my clients who have been able to
    spot the most important systemic problems with these systems.
        I appreciate the opportunity to testify to the Committee
    today. The people that the Committee especially should hear
    from and the policies that the Congress should put in place
    should make sure that at each step in the development and
    selection of these systems, the people who they make decisions
    about are included it. My clients, people with disabilities in
    Idaho, often use the phrase, ``nothing about us, without us,''
    and that is critical in these automated decisionmaking systems
    and AI systems. Thank you.
        Chairman Peters. Tank you. I would certainly like to thank
    each of our witnesses for being here today, and I think, the
    entire Committee is grateful for your expertise and for your
    willingness to come forward to answer our questions.
        I think as we heard today the use of automated systems to
    help government provide public service more efficiently is not
    new. However, as we enter the age of rapid development of
    advanced machine learning methods and other forms of artificial
    intelligence now--not waiting, now--is going to be the time to
    ensure that these systems that the government is using and will
    procure for use in the future do not have unintended, harmful
    consequences.
        It is critical the Federal Government act quickly to set
    appropriate guardrails and oversight policies that protect the
    public. I think we all agree that Americans deserve a
    government that is modern, efficient, innovative, as well as
    one that is transparency, fair, trustworthy, and protects their
    privacy. As Chairman of this Committee I am going to continue
    to work to ensure that the government lives up to those key
    principles, and your testimony today will help inform the
    Committee's future legislative activities and oversight actions
    in the years ahead.
        The record for this hearing will remain open for 15 days,
    until 5 p.m. on May 31, 2023, for the submission of statements
    and questions for the record.
        This hearing is now adjourned.
        [Whereupon, at 11:54 a.m., the hearing was adjourned.]

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