[House Hearing, 118 Congress]
[From the U.S. Government Publishing Office]
HOW ARE FEDERAL AGENCIES
HARNESSING ARTIFICIAL INTELLIGENCE?
=======================================================================
HEARING
BEFORE THE
SUBCOMMITTEE ON CYBERSECURITY, INFORMATION
TECHNOLOGY, AND GOVERNMENT INNOVATION
OF THE
COMMITTEE ON OVERSIGHT
AND ACCOUNTABILITY
HOUSE OF REPRESENTATIVES
ONE HUNDRED EIGHTEENTH CONGRESS
FIRST SESSION
__________
SEPTEMBER 14, 2023
__________
Serial No. 118-64
__________
Printed for the use of the Committee on Oversight and Accountability
[GRAPHIC NOT AVAILABLE IN TIFF FORMAT]
Available on: govinfo.gov
oversight.house.gov or
docs.house.gov
__________
U.S. GOVERNMENT PUBLISHING OFFICE
53-382 PDF WASHINGTON : 2024
COMMITTEE ON OVERSIGHT AND ACCOUNTABILITY
JAMES COMER, Kentucky, Chairman
Jim Jordan, Ohio Jamie Raskin, Maryland, Ranking
Mike Turner, Ohio Minority Member
Paul Gosar, Arizona Eleanor Holmes Norton, District of
Virginia Foxx, North Carolina Columbia
Glenn Grothman, Wisconsin Stephen F. Lynch, Massachusetts
Gary Palmer, Alabama Gerald E. Connolly, Virginia
Clay Higgins, Louisiana Raja Krishnamoorthi, Illinois
Pete Sessions, Texas Ro Khanna, California
Andy Biggs, Arizona Kweisi Mfume, Maryland
Nancy Mace, South Carolina Alexandria Ocasio-Cortez, New York
Jake LaTurner, Kansas Katie Porter, California
Pat Fallon, Texas Cori Bush, Missouri
Byron Donalds, Florida Jimmy Gomez, California
Kelly Armstrong, North Dakota Shontel Brown, Ohio
Scott Perry, Pennsylvania Melanie Stansbury, New Mexico
William Timmons, South Carolina Robert Garcia, California
Tim Burchett, Tennessee Maxwell Frost, Florida
Marjorie Taylor Greene, Georgia Summer Lee, Pennsylvania
Lisa McClain, Michigan Greg Casar, Texas
Lauren Boebert, Colorado Jasmine Crockett, Texas
Russell Fry, South Carolina Dan Goldman, New York
Anna Paulina Luna, Florida Jared Moskowitz, Florida
Chuck Edwards, North Carolina Vacancy
Nick Langworthy, New York
Eric Burlison, Missouri
Mark Marin, Staff Director
Jessica Donlon, Deputy Staff Director and General Counsel
Raj Bharwani, Senior Professional Staff Member
Lauren Lombardo, Senior Policy Analyst
Peter Warren, Senior Advisor
Mallory Cogar, Deputy Director of Operations and Chief Clerk
Contact Number: 202-225-5074
Julie Tagen, Minority Staff Director
Contact Number: 202-225-5051
------
Subcommittee on Cybersecurity, Information Technology, and Government
Innovation
Nancy Mace, South Carolina, Chairwoman
William Timmons, South Carolina Gerald E. Connolly, Virginia
Tim Burchett, Tennessee Ranking Minority Member
Marjorie Taylor Greene, Georgia Ro Khanna, California
Anna Paulina Luna, Florida Stephen F. Lynch, Massachusetts
Chuck Edwards, North Carolina Kweisi Mfume, Maryland
Nick Langworthy, New York Jimmy Gomez, California
Eric Burlison, Missouri Jared Moskowitz, Florida
Vacancy Vacancy
C O N T E N T S
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Page
Hearing held on September 14, 2023............................... 1
Witnesses
----------
Dr. Arati Prabhakar, Director, White House Office of Science and
Technology Policy
Oral Statement................................................... 5
Dr. Craig Martell, Chief Digital and AI Officer, Department of
Defense
Oral Statement................................................... 7
Mr. Eric Hysen, Chief Information Officer, Department of Homeland
Security
Oral Statement................................................... 9
Written opening statements and statements for the witnesses are
available on the U.S. House of Representatives Document
Repository at: docs.house.gov.
Index of Documents
----------
* Questions for the Record: to Dr. Martell; submitted by Rep.
Connolly.
* Questions for the Record: to Dr. Prabhakar; submitted by Rep.
Mace.
* Questions for the Record: to Dr. Prabhakar; submitted by Rep.
Connolly.
Documents are available at: docs.house.gov.
HOW ARE FEDERAL AGENCIES
HARNESSING ARTIFICIAL INTELLIGENCE?
----------
Thursday, September 14, 2023
House of Representatives
Committee on Oversight and Accountability
Subcommittee on Cybersecurity, Information Technology, and Government
Innovation
Washington, D.C.
The Subcommittee met, pursuant to notice, at 1:02 p.m., in
room 2247, Rayburn House Office Building, Hon. Nancy Mace
[Chairwoman of the Subcommittee] presiding.
Present: Representatives Mace, Timmons, Burchett, Edwards,
Langworthy, Burlison, Connolly, Lynch, Khanna, and Mfume.
Also present: Representative Higgins.
Ms. Mace. Good afternoon. The Subcommittee on
Cybersecurity, Information Technology, and Government
Innovation will now come to order. And we welcome everyone for
their participation this afternoon.
Without objection, the Chair may declare a recess at any
time.
And I would like to say that Ranking Member Connolly is
just running a few minutes late, but we have another Member
here. We are going to go ahead and get started, give everybody
plenty of time, and they will be rolling in momentarily.
I would like to recognize myself for the purpose of making
an opening statement.
Good afternoon, and welcome to the hearing of the
Subcommittee on Cybersecurity, Information Technology, and
Government Innovation.
At the very first hearing of this Subcommittee held earlier
this year, expert witnesses told us artificial intelligence, or
AI, is likely to bring disruptive innovation to many fields. AI
should instigate economic growth, higher standards of living,
and improved medical outcomes.
Virtually every industry and institution will feel the
impact of AI. Today, we will discuss the impact of AI on the
largest, most powerful institution in the Nation: the Federal
Government.
As we know, the government today performs an ever-expanding
swath of activities, from securing the homeland, to predicting
the weather, to cutting benefits checks. Many of these
functions could be greatly impacted by AI. That is clear from
the hundreds of current and potential AI use cases posted
publicly by Federal agencies pursuant to an executive order
issued under the last administration.
Federal agencies are attempting to use AI systems to
enhance border security, to make air travel safer, and to speed
up eligibility determinations for Social Security disability
benefits, just to name a few cases.
AI will also shake up the Federal workforce itself. We hear
a lot about how AI could disrupt the private sector workforce,
transforming or eliminating some jobs while creating others.
While the Federal Government is the Nation's largest employer,
and many of those employees work in white collar occupations,
AI is already reshaping because it can perform many routine
tasks more efficiently than humans. That will allow Federal
employees to focus on higher order work that maximizes their
productivity.
In fact, a Deloitte study estimated the use of AI to
automate tasks of Federal employees could eventually yield as
much as $41 billion in annual savings by reducing required
labor hours. A separate study by the Partnership for Public
Service and the IBM Center for The Business of Government
identified 130,000 Federal employee positions whose work would
likely be impacted by AI, including 20,000 IRS tax examiners
and agents. That, of course, begs the question whether we need
to hire tens of thousands of new IRS employees when AI could
transform even or replace the work of much of its current
staff. I think every American could agree with that.
AI can make government work better, but it is still just a
tool, be it an incredibly powerful one, and like any tool, can
easily be abused when used for the wrong purposes or without
the proper guardrails.
AI systems are often fueled by massive troves of training
data that flow through complex algorithms. These algorithms can
yield results, and their own designers are unable to predict
and struggle to explain sometimes, and we are learning this in
real time.
So, it is important we have safeguards to prevent the
Federal Government from exercising inappropriate bias. We also
need to ensure the Federal Government's use of AI does not
intrude on the privacy rights of its own citizens. The bottom
line is we need the government to harness AI to improve its
operations while safeguarding against potential hazards.
That is why Congress enacted the AI in Government Act in
late December 2020, soon before the current Administration took
office. That law requires the Office of Management and Budget
to issue guidance to agencies on the acquisition and use of AI
systems. It also tasked the Office of Personnel Management with
assessing Federal AI workforce needs. But the Administration is
way overdue in complying with the law.
OMB is now more than 2 years behind schedule on issuing
guidance to agencies, and OPM is more than a year overdue in
determining how many Federal employees have AI skills and how
many need to be hired or trained up.
I will also say, in the Administration's cybersecurity plan
before it was made public, I asked the question pointedly to
the Administration if AI was even included in it at the time,
and it was not. It is mentioned three times fleetingly, very
casually in that document today.
The Administration's failure to comply with these statutory
mandates was called out in a lengthy white paper issued by
Stanford University AI Institute. The paper authors also found
that many agencies had not posted the required AI use case
inventories. Others had omitted key use cases, including DHS
submitting an important facial recognition program.
The Stanford paper summed up the Administration's
noncompliance with various mandates by concluding: America's AI
innovation ecosystem is threatened by weak and inconsistent
implementation of these legal requirements.
Most of the AI policy debate is focused on how the Federal
Government should police the use of AI by the private sector,
but the executive branch cannot lose focus from getting its own
house in order. It needs to appropriately manage its own use of
AI systems consistent with the law.
This Subcommittee will keep insisting the Administration
carry out laws designed to safeguard government use of AI, and
I am developing further legislation to ensure Federal agencies
employ AI systems effectively, safely, and transparently. We
have a huge opportunity before us, and I would love to see us
harness the technology that is rapidly evolving. I expect this
hearing will help inform many of these efforts.
Ms. Mace. And with that, we are going to go to--we are
going to go to our witnesses, and when Ranking Member Connolly
comes in, we will give him time for his opening statement.
I am pleased to introduce our witnesses for today's
hearing. Our first witness is Dr. Arati Prabhakar, Director of
the White House Office of Science and Technology Policy and
Assistant to the President for Science and Technology, earning
her the designation as the President's science advisor. Dr.
Prabhakar is also the first science advisor to be nominated to
the President's Cabinet.
This is Dr. Prabhakar's first appearance as a witness
before Congress since her Senate confirmation last year.
We are pleased to have you here today. I am grateful that
you showed up. I will tell you not everybody does, and they
sometimes send the under secretary of the under secretary or
the assistant to the assistant to the assistant. And it is
refreshing to have someone actually show up that we have asked
for, and I just want to thank you for your time today.
Our second witness is Dr. Craig Martell, Chief Digital and
AI Officer with the Department of Defense. And our third
witness is Mr. Eric Hysen, Chief Information Officer with the
Department of Homeland Security.
We welcome everyone. We are pleased to have all of you here
this afternoon.
So, pursuant to Committee Rule 9(g), the witnesses will,
please, if you will stand, and raise your right hand.
Do you solemnly swear or affirm the testimony you are about
to give is the truth, the whole truth, and nothing but the
truth, so help you God?
Let the record show the witnesses all answered in the
affirmative.
So, we appreciate all of you being here today and look
forward to hearing your testimony.
I would like to remind the witnesses that we have read your
written statements, and they will appear in full in the hearing
record. Please limit your oral statements to 5 minutes. As a
reminder, please press the button on your microphone in front
of you so that it is on, and Members can hear you.
When you begin to speak, the light in front of you will
turn green. After 4 minutes, the light will turn yellow. And
when the red light comes on, your 5 minutes has expired, and we
would ask that you just please wrap it up for us.
All right. So, with that, I am going to yield to our
Ranking Member of the Subcommittee, Mr. Connolly.
Mr. Connolly. Thank you, Madam Chairwoman.
I have got three subcommittee hearings today and two caucus
meetings, so I am a little bit out of breath, but thank you.
Thank you for accommodating me.
Earlier this week, Majority Leader Chuck Schumer held his
inaugural AI insight forum and Senator Hickenlooper held a
hearing on the need for transparency in artificial
intelligence.
Today, our Subcommittee returns for a second hearing on AI
to discuss its uses within our own Federal Government. I think
it is very clear all Members of Congress are interested. I am
not sure it is clear how much Members of Congress know about
it.
This Subcommittee is proud to continue its historical
leadership in the AI space. As many of you know, former
Subcommittee Chair, Will Hurd, held a three-part hearing series
on artificial intelligence, and the late former Chairman,
Elijah Cummings, focused primarily on facial recognition.
These initiatives show that, if done right, the Federal
Government can leverage AI to better serve the public. For
example, several Federal agencies are already using AI
technologies to cut costs, improve constituent services, and
strengthen existing systems. The United States Cyber Command
and the Department of Homeland Security, for example, employ AI
technology to protect our networks in counter-cyber attacks.
The United States Postal Service is currently piloting an
autonomous vehicle project that employs AI technology. The
Department of Housing and Urban Development and the U.S.
Citizen and Immigration Services are using AI chatbots to
facilitate communication with the public looking for help from
the agency.
However, like all new tools, if used improperly, AI could
result in unintended consequences. For example, automated
systems can inadvertently perpetuate societal biases, such as
faulty facial recognition technology or opaque sentencing
algorithms used by our criminal justice system. AI can also
threaten jobs, proliferate misinformation, and raise serious
privacy concerns.
That is why I applaud the Biden Administration for
proactively taking significant steps to ensure transparency in
the government's use of AI.
Last October, the White House released a blueprint for an
AI Bill of Rights to ensure the protection of civil rights in
the algorithmic age. Prior to that, the National Artificial
Intelligence Initiative Act codified the establishment of the
American AI Initiative and the National AI Advisory Committee.
This Subcommittee looks forward to hearing an update from
the panelists before us on the joint work with the Secretary of
Commerce to advise the White House on that AI policy.
Everybody can agree the government has a colossal
responsibility in developing the necessary guardrails to curb
the risk of this incredible technology while allowing it to
flourish. This Committee must hold Federal agencies accountable
to ensure that they are making appropriate choices about
whether and when AI is right for their mission.
The Federal Government must also intentionally train,
recruit, and maintain a workforce that is comfortable and
confident with this technology. That is why the Chairwoman and
I worked to pass the AI Training Expansion Act of 2023, H.R.
4503, out of our Committee and would expand AI training within
the executive branch. Really important. And I commend my
colleague for that bipartisan collaboration.
AI is already changing the world around us in so many ways,
and we need to step up to the challenge and mitigate the risks.
The Federal Government needs to ensure this technology is
created, deployed, and used in a safe, ethical, productive, and
equitable manner.
And with that, I yield back. Thank you, Madam Chairwoman.
Ms. Mace. Thank you, Mr. Connolly.
I ask unanimous consent for Representative Clay Higgins
from Louisiana to be waived on to the Subcommittee for today's
hearing for the purpose of asking questions.
So, without objection, so ordered.
I would now like to recognize Dr. Prabhakar to please begin
your opening statement.
STATEMENT OF DR. ARATI PRABHAKAR
DIRECTOR
WHITE HOUSE OFFICE OF SCIENCE AND TECHNOLOGY
POLICY
Ms. Prabhakar. Thank you so much, Chairwoman Mace. And
thanks to you, Ranking Member Connolly, Members of the
Subcommittee. I have really appreciated the work that you all
are doing on artificial intelligence, and it is great to be
here with my colleagues to be able to spend this time to focus
on these important issues.
I have three messages today, and the first one is that AI
is a top priority for President Biden. He is very clear that
this is one of the most powerful technologies of our times.
When we look around the world, we can see that every Nation is
racing to use AI to build a future that is imbued with their
own values, and I think we can all agree that we do not want to
live in a future that is defined by technology shaped by
authoritarian regimes. And that is why the President is very
clear that American leadership in the world today requires
American leadership in artificial intelligence.
Second, for America to lead in AI, government has some core
responsibilities, and one of those, one set of those
responsibilities is to manage the risks of AI. And as both of
your opening statements have noted, AI's risks are broad
because its applications are so broad, and these risks range
from risks related to fraud and information integrity. They
include risks related to safety and security, risks associated
with privacy, civil rights, civil liberties, and risks to jobs
and the economy.
Now, some of these risks can be addressed under existing
laws and regulations. Some of these risks can be managed by
making sure that government uses AI responsibly, and in some
cases, we do expect that legislation will be required. That is
about mitigating risks.
The reason we are doing all of this work to manage risks is
so that our country can seize this technology to build the
future. And if you look at what companies are doing, they are
racing to build better products and services to transform
industries using AI, and this is a technology that holds
equally great promise for the work that government does for the
American people. And that then becomes a second core
responsibility of government.
I think both of you have spoken to that as well in your
opening remarks.
You are going to hear from my colleagues about national
security and homeland security, and there is a lot to be said
there. I will also just briefly touch on the many other
important services and the public purposes that are
government's responsibility. And when you look across Federal
Government today, you will see that agencies are starting to
use the insights that they can glean from these vast troves of
data that they generate in the doing of their business.
AI technology is also changing the way government agencies
interact with their citizens. They can speed it up. It can
simplify it. It can just make those administrative processes
work much better. The examples are very wide-ranging. They
include AI for weather prediction. They include AI to help us
keep air travel safer. AI is being used to speed up the
processing of disability determinations. It is being used to
improve how we process patent applications, and those are just
an example today.
If you take a peek inside of labs around the country and
look at what is happening with federally funded R&D, in the
world of research and development you will get a glimpse of
where the future is going, and AI is playing a huge role there
as well because AI can enable the design of the materials that
we need for advanced batteries, for hydrogen storage, the
things that are critical to our clean energy future.
AI can change the way that we predict disasters, the way
that we implement plans for resilience as the climate changes.
AI can transform drug design. It can allow us to tailor
clinical care to each individual patient's needs. It can enable
major advances in population health.
Used responsibly, AI can help us deliver better outcomes
and to create new possibilities for the American people.
My third message for you, and I will end with this, is that
the Biden-Harris Administration is taking action to meet this
moment. We have moved with urgency on a series of steps that
started with the AI Bill of Rights that we published almost a
year ago, and I want to emphasize that, especially in a time
when technology is moving as fast as it is, it is so important
to be clear about our values, about the importance of rights,
about safety and security, about privacy. And that was the
important role of the AI Bill of Rights.
More recently, because of the President's leadership, 15
companies have now made voluntary commitments to focus on
safety, security, and trustworthiness in their AI systems that
they are developing and driving. That is companies'
responsibilities.
Today, the White House is working----
Ms. Mace. We are running out of time. I apologize. We are
going to be voting soon, so if you can----
Ms. Prabhakar. I will wrap up.
Ms. Mace. Yes.
Ms. Prabhakar. Absolutely.
Ms. Mace. Thank you.
Ms. Prabhakar. We are working today in the White House on
an executive order. The Office of Management and Budget is
working on guidance for departments and agencies. That is the
executive branch. We continue to work with our international
allies because AI does not stop at the borders. And finally, we
remain committed to working closely with Congress on a
bipartisan basis as you consider legislation.
I will just finish by saying this work is urgent, it is
important, and I very much look forward to working with you on
it.
Ms. Mace. Thank you.
And I will recognize Dr. Martell to please begin your
opening statement.
STATEMENT OF DR. CRAIG MARTELL
CHIEF DIGITAL AND AI OFFICER
DEPARTMENT OF DEFENSE
Mr. Martell. Chairwoman Mace, Ranking Member Connolly, and
distinguished Members of the Subcommittee, thank you very much
for inviting us here today.
And I would like to start just by asking the question, what
is AI? And so, we should have a sort of common definition in
our head as we are going through this. So, when I say the
phrase ``artificial intelligence,'' I simply mean statistics at
scale.
We gather massive amounts of data from the past. We use it
to build a model, and we use it to predict the future. It is
really important to think about it that way because it is
statistics at scale, which means it is never 100 percent
correct, which means for every model that we build, it will
always, sometimes, get it wrong. And so, a large part of what
we have to think about is how do we understand when it gets it
wrong, and what should we do when it does get it wrong. So, it
is really important to rethat as I am going through my
comments. My other panelists here may have different
definitions, but that is the operative one for me.
I look forward to sharing the ongoing efforts of the Chief
Digital and AI Office around the responsible use of data
analytics and AI-enabled technologies to accomplish our
national defense mission.
Data analytics and AI are integral to accomplishing the
priorities set forth in the National Defense Strategy. To
support these efforts, the CDAO has established five strategic
initiatives: Improving data quality; that is the stuff we use
to measure the past. Developing robust performance metrics;
that tells us how well we are doing in the future. Providing
enterprise-ready AI scaffolding; building the data integration
layer for CJADC2; and developing a robust talent management
plan for the Department of Defense as a whole.
First, quality data is CDAO's foundational priority. We are
focused on holistically improving the quality of the data that
enables most DOD use cases. For example, CDAO is providing data
and digital talent teams to the principal staff assistants and
the combatant commanders through the Accelerating Data and AI
Initiative, also called ADA.
Additionally, the CDAO is creating validation and
verification processes that check data for errors,
inconsistency and, with respect to bias, class imbalances,
before AI models are ever even produced. We are also working
closely with the U.S. Cyber Command on their 5-year AI roadmap
for rapidly acquiring and adopting AI systems.
Second, in business performance, CDAO, in partnership with
the DOD performance improvement officer, is defining and data-
enabling the metrics that the DOD will use to assess and manage
its performance in support of the Secretary of Defense's
priorities, the National Defense Strategy, and the strategic
management plan. CDAO is ensuring that these metrics are
outcome-based, not just how many meetings did I go to, but the
effectiveness of those meetings, and measurable.
Third, enterprise AI scaffolding consists of the robust
environments and tools that enable cutting-edge development of
machine learning and AI capabilities. We provide the technical
and nontechnical enterprise services necessary to accelerate
secure, reliable, and responsible AI development.
Fourth, for CJADC2, CDAO is focused on building the data
integration layer that will enable data-centric command and
control across the Department and with our partners and allies.
CDAO is iteratively assessing the necessary capabilities for
this data integration layer via a series of experiments called
GIDE, Global Information Dominance Experiments. And these
experiments are in their seventh iteration and currently
underway now. GIDE 8 is scheduled for December, and I am happy
to brief the Committee on the successes that we have been
having in GIDE.
Finally, in order to enable data-driven capabilities across
the entire Department of Defense, we are building a unified
digital workforce program with the chief talent management
officer and other under secretaries. The goal of this program
is to develop a digital workforce that is globally identifiable
and readily accessible for DOD use.
Ladies and gentlemen, within all of these initiatives, I
want to clarify that AI is not a singular, monolithic
technology, nor a one-size-fits-all solution. That is extremely
important. When we say AI, it is not something that if we have
it, we win, and if they have it, we lose.
We need different algorithms, different success criteria,
and different data to train the different models underpinning
each of our different use cases. Think about the different use
cases in your daily lives: talking to your phone, getting
shopping suggestions, does this shirt go with those pants, and
using a search engine to find the information you need. Each of
these require very different AI technologies.
The same is true for the DOD. We need computer vision to
understand our environment; natural language processing to
navigate the Department's policies and idiomatic language,
which is really hard for humans to understand; and
reinforcement learning for predictive maintenance; as well as
many other types of machine learning algorithms.
It is very important to remember that AI is neither a
panacea nor a Pandora's box, and if we think about it that way,
we are not thinking about it correctly and we are not going to
be able to tackle the problem. It is not a one size thing. We
need to evaluate its effectiveness and concomitant dangers on a
use case by use case basis.
Ms. Mace. We have got to wrap it up. I apologize.
Mr. Martell. I am done. That was my last word.
Ms. Mace. Great, thank you. There you go. Awesome. Bravo.
I would like to recognize Mr. Hysen to please begin your
opening statement.
STATEMENT OF MR. ERIC HYSEN
CHIEF INFORMATION OFFICER
DEPARTMENT OF HOMELAND SECURITY
Mr. Hysen. Chairwoman Mace, Ranking Member Connolly, and
distinguished Members of the Subcommittee, thank you for the
opportunity to testify today.
I would like to note that in addition to serving as the
Department's Chief Information Officer, Secretary Mayorkas also
named me today as the first DHS Chief Artificial Intelligence
Officer.
I would like to talk with you today about three concrete
use cases where DHS is already using AI to deliver clear
benefits for the American people and then share the
comprehensive measures we are taking to ensure that our use of
AI is safe, responsible, and rights respecting.
First, DHS is using AI to keep dangerous drugs out of our
country. Recently, a car drove north from Mexico and approached
the San Ysidro port of entry in San Diego, California. In the
past, the Customs and Border Protection officer that inspected
that car would likely have had no reason to give it extra
scrutiny. But this time, one of our machine learning models
noticed a potentially suspicious pattern in the vehicle's
crossing history. After looking at the model's flag, the
officer decided to refer the car to secondary inspection, where
we discovered and seized nearly 60 kilograms of fentanyl and 16
kilograms of meth concealed in the vehicle's rear quarter
panels and gas tank. If not for this use of AI, those drugs
could be on our streets.
Second, DHS is using AI to aid our law enforcement officers
in investigating heinous crimes. Last month, Homeland Security
Investigations announced the completion of one of the most
successful operations ever against child sexual abuse online.
Operation Renewed Hope resulted in identifying 311
previously unknown victims of sexual exploitation and led to
the rescue of several victims from active abuse and the arrests
of suspected perpetrators. This operation relied on the
expertise and dedication of our agents and our partners
domestically and abroad, but our agents had an extra tool at
their disposal.
Machine learning algorithms were used to enhance older
images and give investigators new leads. Through this use of
AI, we were able to turn formerly cold cases into rescues and
arrests.
Finally, DHS is using AI to make air travel easier and
safer. TSA has started rolling out touchless pre-check in
select airports, a new optional way of going through the
airport, curb to gate, without ever taking out your wallet.
Once you opt in, you can check your bag, go through the
security checkpoint, and board your flight all with just a
quick photo.
This process and TSA's acceptance of mobile driver's
licenses in seven states, and counting, used thoroughly tested
AI powered algorithms to save time, reduce physical touch
points, and increase security by verifying identity more
accurately.
While I have highlighted these three examples today, DHS
will use AI to transform all parts of our operation, from
detecting and mitigating cybersecurity vulnerabilities to
enhancing maritime search and rescue operations and far beyond.
AI will provide smarter and timelier information to our agents
and officers to aid them in making decisions and free them up
from routine tasks to focus on higher value work.
As we move forward, we will ensure that our use of AI is
responsible and trustworthy; that it is rigorously tested to be
effective; that it safeguards privacy, civil rights, and civil
liberties, while avoiding inappropriate biases; and to the
extent possible, that it is transparent and explainable to the
people we serve.
Last month, Secretary Mayorkas issued our key principles
for responsible AI use. We are applying these principles
through the DHS AI Task Force, which I lead alongside our Under
Secretary for Science and Technology, by issuing comprehensive
policies on specific types of AI, as we did just this week with
new restrictions on our use of facial recognition.
We will work alongside our internal and external oversight
partners, to include Congress and this Subcommittee, as we work
to implement NIST's AI risk management framework and remain
fully compliant with evolving laws, practices, and policies.
Thank you again for the opportunity to testify today. I
look forward to your questions.
Ms. Mace. Thank you, Mr. Hysen.
I know votes have just been called. I am going to, before I
gavel out--and my colleagues can leave to go vote. I am just
going to ask my questions before we go and gavel out.
Dr. Prabhakar--I am going to recognize myself for 5
minutes.
My first question is to you, Dr. Prabhakar. As the
President's science advisor, you are the President's top
artificial intelligence advisor, I expect you regularly brief
him on AI. The Associated Press has quoted you as saying in a
recent interview you have had several conversations with him
about AI.
How many times have you been able to brief him thus far in
this position?
Ms. Prabhakar. Thank you for the question, Chairwoman. The
President has been very focused on AI. He has asked for
briefings on AI at multiple junctures.
Ms. Mace. How many times have you been able to brief him?
Ms. Prabhakar. I would have to stop and count. Let me give
you a couple of examples. He met----
Ms. Mace. Is it more than one?
Ms. Prabhakar. Multiple times. He met with his council of
advisors, PCAST, and the President's Council of Advisors on
Science and Technology. I believe that was in early April. We
had a discussion about AI before that, and then he spent an
extended period with a room full of amazing science and
technology experts, people using AI, people generating AI, and
had a very extensive conversation there.
Another occasion was----
Ms. Mace. What did President Biden say to you about AI?
Ms. Prabhakar. President Biden has spoken publicly many
times about AI and----
Ms. Mace. What has he said to you in these conversations
about AI?
Ms. Prabhakar. Obviously, I am not in a position to say
what he said in the Oval. I will tell you what he has said
publicly, which is very consistent, which is he recognizes how
fast it is moving, how it is part of this pivot point in
history, and the choices that we make are essential. He is very
excited about the potential----
Ms. Mace. How would you characterize his level of
understanding of AI? Do you think he understands?
Ms. Prabhakar. I think it is excellent. The questions--he
grills me, and he grills everyone else who----
Ms. Mace. He grills you?
Ms. Prabhakar. Yes.
Ms. Mace. What does he grill you on?
Ms. Prabhakar. Well, I can talk about the things that he
has said publicly, and they are on many topics. He has talked
about the ways that AI can be used. He has expressed concerns
about the way that it can create problems. He has talked about
the fact that he is married to a schoolteacher, and so he knows
about how it shows up in education.
Ms. Mace. Does he understand its uses within the Federal
Government? That is sort of outside, I mean, education. I mean,
in the Federal agencies and how it can be utilized, does he
understand that? Does he talk about anything relevant to the
progressive AI?
Ms. Prabhakar. The President is very clear about the
breadth of applications of artificial intelligence, and his
vast understanding, of course, is many years as a legislator
and now as----
Ms. Mace. Vast.
Ms. Prabhakar. President, of all the functions of
government, of the role that it plays in national security, but
also in all the other functions of government. He understands,
obviously, that it is clearly going to be powerful.
Ms. Mace. The Office of Science and Technology Policy is
not a regulatory agency. It is a White House policy shop. So,
can you explain what role you and your office play with respect
to Federal AI policy? How does that work?
Ms. Prabhakar. We have several roles. And as OSTP, a core
role is to be the place where the Federal R&D enterprise comes
together, where we work together and make sure that people know
what each other are doing in areas across research and
technology but including information technology and artificial
intelligence.
When a massive new shift like this great acceleration in AI
happens, one of our important roles is to be clear with our
colleagues in the White House, with the President, with our
colleagues in departments and agencies about how the technology
is progressing, what issues they will need to contend with,
what the big opportunities are.
And that means that in the case of AI, our National AI
Initiative Office, which Congress established at OSTP a couple
years ago, that cadre of people in my organization have been
extraordinarily busy mapping out the risks, the opportunities,
and informing policy----
Ms. Mace. So, a question about some of that. What are some
of the operations of your office? It maintains governmentwide
AI use case inventory. Is that correct?
Ms. Prabhakar. Working with the Office of Management and
Budget.
Ms. Mace. That inventory has been appropriately criticized
in the press as being inconsistent and incomplete. The
inventory is lacking uniformity, and some significant AI use
cases have been omitted.
So, is your office doing anything to improve the
inventories, to improve transparency with the public? What does
that look like?
Ms. Prabhakar. The initiative to start cataloging those use
cases was an important one, and it is very much work in
progress. We are getting good insights from what is already in
that use case inventory and working with departments and
agencies----
Ms. Mace. And then one last question. I have got 25
seconds.
OMB is more than 2 years late in complying with a
congressional mandate to give Federal agencies guidance on the
acquisition and use of AI. The law requires OMB to coordinate
with your office in drafting that guidance.
So why--and very quickly. We have 10 seconds. Why is the
process stalled? When can we expect to see some guidance?
Ms. Prabhakar. The Office of Management and Budget is
working in a very focused manner on what they clearly
understand----
Ms. Mace. Two years late.
Ms. Prabhakar.[continuing] is a priority.
Ms. Mace. Thank you so much.
Ms. Prabhakar. We will get there.
Ms. Mace. Our time is up, and I yield back.
And pursuant to the previous order--and I apologize because
we are out for votes--the Chair declares the Committee in
recess, subject to the call of the Chair. We will stand in
recess for votes.
Thank you.
Mr. Edwards.
[Presiding.] Welcome back, everyone. Pursuant to the
previous order, the Chair declares the Committee in recess--OK.
Let us start that over.
The Committee will come back to order.
And the Chair recognizes Representative Langworthy for 5
minutes.
Mr. Langworthy. Thank you, Mr. Chairman.
I would like to thank all of our witnesses for being here
today to continue driving the artificial intelligence
conversation forward. The opportunity that the Federal
Government has to implement AI into its everyday operations is
potentially exciting for the future of the country and for the
modern workforce.
However, I would like this Subcommittee, and all of us, to
consider the impact of AI and other emerging technologies on
our younger generation. While AI has numerous benefits that I
am sure will be discussed here today, it has serious
implications on our youth, especially when it comes to
generative images and child exploitation. I would be more than
happy to work with Chairwoman Mace and the rest of our
Oversight Committee to address these concerns.
But before we do that, I want to speak about some of the AI
frameworks that have been developed. Specifically, the National
Institute of Standards and Technology has a well-established
track record of developing frameworks and recommendations to
improve cybersecurity outcomes in the Federal Government.
Earlier this year, NIST published a groundbreaking AI risk
management framework, which was developed at Congress'
direction in an open multistakeholder process.
Leading companies are already using the NIST AI framework
for managing AI risks, just as they use the NIST cybersecurity
framework and other NIST cyber recommendations.
With that being said, Dr. Prabhakar, I would like to ask
you whether or not you see the NIST AI framework being taken up
by the Federal Government in the same way that NIST
cybersecurity work is being used today, and what steps, if any,
that your office is taking to implement the AI framework?
Ms. Prabhakar. Thank you so much, Representative
Langworthy. NIST--I had the great pleasure of leading NIST many
decades ago when my hair was still black, and I share your
important point about the role that that organization has
played in cybersecurity and other important areas. In
artificial intelligence, their risk management framework, when
they put that out, I think that was one important step in a
longer journey to getting to where we can actually have safe
and effective AI, whether it is private sector use or public
sector use.
And as you have seen with industries' adoption of the risk
management framework and its--I see that approach also starting
now to be used within government. What that allows people to do
is to know what questions to ask about how to make an AI system
safe and effective. And again, depending on the application,
the questions will be different and the process that they go
through will be different. But that is a starting point. And to
me it is just table stakes to know that, you know, if your
organization is using that risk management framework, it is
table stakes to know that you are actually asking the question.
I want to step back, though, and also be clear that what we
all are--we all understand that what we need is a future where
AI systems are safe and effective, that they do what you need
them to do, that they do not do dangerous things or
inappropriate things that you do not want them to do. But I
think we should all be very clear that companies, researchers,
nobody actually really quite knows how to do that.
And so, I think NIST's work and the technology community's
work that is still ahead is to continue to develop tools and
methods so that we can get as good at understanding whether an
AI system is safe and effective as we know for physical
products in many other areas, and that is some of the work that
still remains to be done.
Mr. Langworthy. I wanted to follow up and ask about
criticism toward the AI blueprint that OSTP has produced, the
blueprint that has been criticized for being in conflict with
the NIST framework. Could you address this?
Ms. Prabhakar. I would be happy to address this. The AI
Bill of Rights focused on our values, which are so important
when we are in very choppy times and choppy waters as this
technology is moving so fast. And if you go back and look at
the Bill of Rights, what it talks about is how important it is
to make sure that people have--are not discriminated against
but have access to safe systems that are secure.
So, a lot of the same themes that you will find in the risk
management framework and everything that we have been talking
about here today, that is very consistent with the Bill of
Rights. That work was developed by OSTP but working very
closely with NIST and others across government with many, many
inputs from private organizations, companies, civil society
organizations, academics.
And then when NIST built the risk management framework on
the heels of that, again, there was a lot of close
communication and coordination. And to me it was--part one was
values of the Bill of Rights. Part two was the initial steps of
how does an organization start grappling with what are the
processes that they need to put in place to manage these risks.
Mr. Langworthy. Unfortunately, I am out of time, and I
yield back, but we will be following up with some questions in
writing.
Ms. Prabhakar. I look forward to it.
Mr. Edwards. The gentleman from New York yields, but I
would like to yield my 5 minutes back to Mr. Langworthy.
Mr. Langworthy. Well, thank you very much.
I also wanted to bring up an executive order issued by the
last administration requiring Federal agencies to post for
public view most of their AI use cases. This is intended to
give the public a view into the Administration's current and
planned use of AI systems. But many of these agency inventories
are missing or they are incomplete, according to a Stanford
University AI Institute whitepaper which was issued last
December.
Do you agree that the public has a right to know for what
purposes AI is being used by the Federal agencies and that it
is important that these inventories are done consistently,
completely, and accurately? And will you pledge to work to
continue to ensure that that is the case?
Ms. Prabhakar. Thank you very much, Mr. Langworthy, for
that question.
I share your focus on the value of those use cases for all
the reasons that you mentioned. It is important for the public
to know and across government for people to understand how AI
is being used, and there is important progress that we are
making and will continue to make as a Federal Government on
those AI use cases.
Thank you.
Mr. Langworthy. Transparency I think is something that we
all need to fight for, especially as this emerging technology
is coming at us so quickly.
I want to see if regulatory sandboxes have been part of
your conversations. The European Parliament approved its AI
Act, which includes a conversation about setting up coordinated
AI regulatory sandboxes to foster innovation in artificial
intelligence across the EU.
Do you see regulatory sandboxes having success in the EU
and whether or not do you think they will be successful in the
United States?
Ms. Prabhakar. My colleagues may have answers on that, Mr.
Langworthy. I do not think I have enough information to give
you a complete answer. I will just note that we continue to
work with our colleagues and allies in Europe and around the
world simply because AI is happening everywhere, and different
regions are taking somewhat different approaches. But we are
finding that with our like-minded allies, we all share this
focus on getting to a safe and effective AI future, and I think
there will be some important collaborations that are possible
there.
I do not know if others have other comments on that topic.
Mr. Martell. So, we think being able to work effectively
with AI with our partners and allies is extremely important.
So, we have been focusing a lot, not only on the data sharing
and how do we do that effectively according to regulations, but
also how do we build models together and evaluate the
effectiveness of those models together. And so, we have a
number of initiatives working through that.
Mr. Langworthy. Mr. Hysen?
Mr. Hysen. No, nothing to add on regulatory approaches. We
defer to the White House.
Thank you.
Mr. Langworthy. OK. With the remaining time, I want to
focus on the Department of Homeland Security. So, Mr. Hysen,
are you concerned that as AI systems become more mature and
complicated, that criminals will have greater opportunity to
commit heinous crimes, like child exploitation?
Mr. Hysen. Congressman, we absolutely are concerned there;
however, we are also looking to harness AI to combat those
crimes. I shared earlier our work of Homeland Security
Investigations in Operation Renewed Hope, which used AI to help
rescue victims from active abuse, as well as to arrest
suspected perpetrators. So, as we are looking to better defend
against the use of AI to commit these crimes, we are also using
it to defend against them.
Mr. Langworthy. The protections, you know, have to be built
at the same time as, you know, all of the fruits of what AI can
bring us. They have to be there. Our most vulnerable, I
believe, are those most likely to be harmed by, you know, a lot
of this AI technology.
Now, I will expand the scope of this question and include
America's adversaries unleashing increasingly powerful cyber-
attacks against U.S. critical systems. What is DHS doing in
preparation to respond with the use of AI in those respects?
Mr. Hysen. Absolutely. We are, and have been for the entire
Administration, concerned about adversarial use of AI against
Federal and critical infrastructure networks. Secretary
Mayorkas established our Artificial Intelligence Task Force,
which I co-lead, and charged us with looking at the use of AI
to secure critical infrastructure as one of our critical
objectives. We are working with the Cybersecurity and
Infrastructure Security Agency to look at how we can
effectively partner with critical infrastructure organizations
on safeguarding their uses of AI and strengthening their
cybersecurity practices writ large to defend against evolving
threats.
Mr. Langworthy. Very good.
I yield back, Mr. Chairman.
Mr. Edwards. The gentleman yields.
Next, the Chair recognizes the Honorable Mr. Khanna from
California for 5 minutes.
Mr. Khanna. Thank you, Mr. Chair.
Dr. Martell, I thought your description of AI as statistics
on scale was one of the best I have heard. Was that your phrase
or is that someone else's?
Mr. Martell. You know, these things get bounced around. I
think it is mine, but it might not be, so I do not want to
claim anything that is not, but it is one I have been using for
a while for explanatory purposes.
Mr. Khanna. Well, I appreciate it, because I think--you
know, I do not always agree with Noam Chomsky, but I thought
his op-ed in the New York Times where he talked about human
intelligence and what that entails and how that is so different
than a predictive model that is taking a lot of data and
putting probabilistic outcomes was very thoughtful.
And one of the concerns I have is that there is been an
overhyping of AI as a form of human intelligence, which I just
think is giving our species less credit than we deserve. So, I
appreciated your clarification.
Dr. Prabhakar, Chairwoman Nancy Mace and I have a bill
called the SEARCH Act, which would basically require government
agencies to use AI technology to help improve the search
functions in their own websites in collecting data. Could you
help describe what the benefits of having AI do that kind of
search for government agencies could be?
Ms. Prabhakar. Representative Khanna, thank you for your
leadership on that matter, as well as other issues related to
AI.
And I think you have described it very clearly. If you step
back and you think about how much the government does that is
about interacting with citizens, providing information, taking
information, those are areas where this new generation of
language-based AI, of course, can have tremendous benefits, but
it has to be used thoughtfully and carefully.
And search is a great example. It is easy to imagine the
use--and people are starting to do this--using generative AI to
summarize complex documents, to synthesize arguments from
across many different perspectives, to draft responses. And I
emphasize draft because as anyone who has worked with these
technologies knows, I think what we are seeing, private sector
and public sector I think are finding that there are few cases
we are simply relying on a chatbot will solve a problem, but
there are many cases where that interaction might be the
beginning of accelerating a workflow or improving the way that
you do whatever you do.
So, I think those are interesting examples, and they are
different and distinct and build on top of the many ways that
government agencies are using AI on sensor data or data that
they collect that is not language-based. So, I think this is
this next chapter that is starting to unfold, and I appreciate
your focus on it.
Mr. Khanna. I appreciate that.
And, Dr. Prabhakar, when you look at AI--and obviously
these things are hard to predict--how do you think over the
next 10 years it will have an impact on jobs? Is it a case of
augmenting people's talent?
I have often said to Hollywood, my concern is not that if
they had AI bots write all the scripts, that it is not able--
that they would not be able to do it. My concern is it will
just be terrible. You know, they are not going to produce
Hamlet. It will just be the further devolution of
entertainment.
Many a times I have used ChatGPT, and I have challenged my
staff to use it for a speech, and it is not as good as Cliff's
Notes. And if professors are having students use it and not
getting good grades, it is probably because they are not asking
the right questions. I mean, probably the class is not
challenging enough.
But my point is that, where is it that it is going to
displace things? How do we prepare for it? Where is it that it
is going to create opportunity as you see it?
Ms. Prabhakar. This focus on the impact of AI technology on
jobs is critically important because we have a long history. We
know that technology does change work in all kinds of ways. And
it is, I think--let me just start by saying that it is very
early, and right now we do not fully know. It has not fully
played out how this new generation of language-based AI will--
how will it blossom and what impacts will it have.
The best understanding that many experts have in this area
is that there are things that will look a lot like prior
changes with technology coming in, and there are things that
are not going to look the same.
What I think we can expect is that some jobs may get
upskilled, become more valuable, allow people to earn more for
their labor, and other jobs will get displaced. That has
happened with every wave of technology for not just decades but
probably for millennia.
And I think what is very different about this new
generation, of course, is the fact that it can be used to do
administrative tasks, creative tasks, everything from graphic
design and image generation to writing documents to even legal
analysis, and so a lot of the kinds of professions that a few
years ago I think people imagined were not going to be touched
by AI technology now will come into the limelight.
Mr. Khanna. My time has expired. I am still waiting for
ChatGPT to come up with something as eloquent as statistics
with scale, but we will see.
Ms. Prabhakar. That is right.
Mr. Martell. I do not think that is possible, sorry.
Mr. Edwards. And so, with that, the Chair now recognizes
the Honorable Representative Timmons from South Carolina for 5
minutes.
Mr. Timmons. Thank you, Mr. Chairman.
Thank you to all our witnesses for being here.
Dr. Martell, I want to start out with you. You defined AI
in a way that I have never heard before and in a way that is
not really what other searches would define it as. Can you
elaborate on that definition?
Mr. Martell. Sure. So, it actually does not define all of
AI. It defines modern AI. There is a lot of prior generational
AI that is actually rule-based, expert systems where they have
written a bunch of if-then statements. I would not call that
statistics at scale.
But modern AI is--all of modern AI--it is based on
gathering massive amounts of data from the past. That is our
lens into the world. And particularly, it is highly curated
labeled data, which represents the task at hand. It is using
that to build a model.
And you can just think back to any simple class you had
where you did linear regression. That linear regression is the
model, and so it builds the model and then it uses that model
to predict the future. And I do not think anybody in the
scientific community would disagree with that as a general
characterization of how modern AI applies.
Mr. Timmons. I appreciate you elaborating. I see where you
are--I see your point and I agree. I mean, I had not thought of
it that way.
Can we talk about possible uses of AI within either DOD or
our adversaries' military capabilities?
Mr. Martell. Sure. One of the reasons--if I may, one of the
reasons I describe it like that is to have people realize that
AI is not monolithic. So, when we say AI, what we really mean
is a specific AI-based technology or a specific statistically
based technology. And it is important to differentiate that,
because we may be doing really well for one use case and very
poorly in another, and that may be so for our adversaries as
well.
And so, if we focus mostly on AI as a monolithic thing, if
we have it, we win; if they have it, we lose, then we are
actually missing where we should be aiming our attention at:
particular capabilities that we want to deliver or capabilities
that we want to defend against. And so, we spend a lot of our
energy characterizing those.
That is a conversation I am happy to have with you in a
different venue.
But there is lots of use cases within the business aspect
of the Department of Defense. Doing analysis of the documents
with modern, language-based artificial intelligence is really
effective. Understanding the environment using computer vision
is really helpful. But in that case, when you think about
understanding a document or an image being analyzed and some
action being taken from that analyzed image, it is really
important to remember that that was a statistical answer.
So, let us say that we say that there is something in that
image, right. We are looking for a truck or a school bus, and
we say it is a truck, but it is actually a school bus. And the
system got it wrong. Called it a truck when it is a school bus.
It is really important to us to build systems that are not
simply dependent upon that algorithm but that have humans
wrapped around it. It is really human machine teaming so that a
human can say, oh, no, it got it wrong. And then there is a--
because remember, they are statistical, so they will--it will
always be the case that every model will sometimes get it
wrong. Always be the case that every model will sometimes get
it wrong. So, you need to have a human machine teaming
structure so that that human can correct the system and feed
back the system and make the system better.
Mr. Timmons. And I think as it relates to weaponizing it,
one of the benefits is the speed at which it can act. And if
you have a drone swarm that is AI enabled, I mean, how do you
incorporate the human component? Because the whole benefit of
using AI in that scenario would be the speed at which it is
able to act.
Mr. Martell. Correct. I think that is an excellent question
and thank you for it, Congressman Timmons.
One thing the military does well is train with technology.
And so, you can think about the way our training works over and
over and over and over and over again as a way for you to
develop justified confidence in a tool, right? If you have
justified confidence in your weapon, sometimes it is going to
jam, but you still get a sense of the likelihood or the
conditions under which it might, and you learn how to use it.
Mr. Timmons. I see where you are going. Planning for the
training component to make sure that you have answered the
question 4,000 times before it is actually done with live fire
is the solution.
Mr. Martell. That is right. And sometimes it will get it
wrong, and then whomever made the decision to deploy that
system will be responsible, as we always are. There is always a
responsible agent making a decision to deploy a system.
Mr. Timmons. And I guess there is--what is concerning is
that while our military will likely make sure that there is a
human component and a training component, a nonstate actor that
does not care about collateral damage----
Mr. Martell. Correct.
Mr. Timmons [continuing]. And/or consequences of their
actions may be able to use the same technology without regard
to the necessary collateral damage.
Mr. Martell. That is 100 percent correct. And then we see
that as a particular use case that we should train against.
What are the tools and countermeasures we need for that
situation? That is why I think it is really important to not
think about it as monolithic but as use case by use case based.
Mr. Timmons. Sure. Thank you. Thank you all for being here.
I yield back, Mr. Chairman.
Mr. Edwards. The gentleman yields.
Next, the Chair recognizes the Honorable Representative
Higgins from Louisiana for 5 minutes.
Mr. Higgins. Thank you, Mr. Chairman. I appreciate the
Subcommittee waiving me on for me to address this topic.
Ladies and gentlemen, thank you for being here.
Dr. Prabhakar, that is a lovely name, and we appreciate you
being here.
Madam, in your opening, in your statement, in your written
statement, you say that--one of your quotes, I believe, says AI
advances also bring a risk of a deepening erosion of privacy as
surveillance increases and as more and more sensitive
information is used to train AI systems. You point out that
authoritarian governments are already using AI to censor and
repress expression and abuse human rights.
Is that part of your statement, ma'am?
Ms. Prabhakar. Yes, sir, it is.
Mr. Higgins. OK. I am just clarifying.
I have a broader concern I would like to focus on in my
limited time here regarding government's use of AI in the
enforcement of laws and regulations, and I think I am strongly
against that. And I am going to ask you, Mr. Hysen, regarding
law enforcement. That is my background. You may not know. But I
appreciate the work that has done on the ground at the
enforcement level, and I have my concerns there.
But for you, Doctor, you referenced the authoritarian
government's use of AI. Talk to us about criminal enterprise or
state-sponsored cyber threat enterprise and how that would
relate to AI. For instance, like malware AI or Trojan horse AI.
We have all--we have seen major compromises of cyber systems at
the government level and in the private sector.
In my state of Louisiana, all driver's licenses--if you
have a driver's license in Louisiana, your data was
compromised. That is pretty much everybody. So, we have stories
like this across the country, it affects us all. Seems to me
that AI is a tremendous threat in that arena.
Can you address that?
Ms. Prabhakar. Thank you for the question, Congressman
Higgins. You are focusing on some of the important issues about
the power of AI and the--which makes it very appealing to solve
hard problems but then comes with these risks that you have
highlighted.
Many threads in some of your comments. Let me focus for a
moment on the cybersecurity element, because I think it is a
great example of the bright and the dark side of AI technology.
What we are seeing with the advances in AI is the ability
to write software code more quickly, more securely, more
robustly. Those are some of the bright-side advantages. And at
the same time, this is a technology that can be used for cyber-
attacks to generate--to look for vulnerabilities, to generate
attacks more efficiently.
And so, I think that is the landscape. And then the choices
that all of our work focuses on, of course, is how do we
mitigate those risks and secure it. For example, securing our
systems--our cybersecurity systems as well as we can.
Mr. Higgins. In the interest of time, you are aware--and
your team and the executive branch and the President is aware,
we hope--we have to be very focused on the balance moving
forward between the power of AI and the potential dangers of
AI.
And I think, primarily, we have to establish security
against weaponized AI from criminal networks and from nation-
states that will use AI against our Nation. And at the same
time, we have to make sure that we do not build AI into our own
governmental enforcement systems that would threaten the
individual rights and freedoms of Americans.
Mr. Hysen, briefly, you mentioned that AI recognized
patterns in the crossing at the border. How would that relate
to the instinct--you believe that AI could dull the human
instincts and judgment in law enforcement operations similar to
the way that--like, many engineers now cannot use a slide rule.
We do not remember phone numbers anymore. They are in our
contact data. Most Americans cannot read maps and operate a
compass anymore. We use GPS. Kids in school cannot--they are
not taught cursive script. And yet all our historical documents
are written in cursive script.
Do you understand where I am going with this? Please,
briefly, if the Chairman will allow, address that as it relates
to the instincts of law enforcement.
Mr. Edwards. The witness may answer the question.
Mr. Hysen. Congressman, thank you. I certainly acknowledge
the risk and want to assure you that we are leveraging AI as
decision support for our law enforcement officers, but that
ultimately, our officers are the ones responsible for making
law enforcement decisions.
I also see tremendous potential to use AI to remove
repetitive paperwork and administrative tasks that our officers
have to do that they would tell you, and they would tell me,
dulls their focus from their security mission.
Mr. Higgins. Thank you, sir. That is the answer I was
hoping for.
Mr. Chairman, I appreciate the indulgence. I yield.
Mr. Edwards. The gentleman yields.
The Chair would like to thank the witnesses for your time
this afternoon.
And without objection, Members will have 5 legislative days
within which to submit materials and additional written
questions for the witnesses which will be forwarded to the
witnesses.
Without objection, the Subcommittee stands adjourned.
[Whereupon, at 2:41 p.m., the Subcommittee was adjourned.]
[all]