Rise of the Machines

Artificial Intelligence and its Growing Impact on U.S. Policy

Chairman Will Hurd and Ranking Member Robin Kelly

 

Subcommittee on Information Technology

Committee on Oversight and Government Reform

U.S. House of Representatives

September 2018
1

EXECUTIVE SUMMARY

Beginning in February of 2018, the Subcommittee on Information Technology of the 

House Committee on Oversight and Government Reform held a series of hearings on artificial 

intelligence (AI). In connection with those hearings, majority and minority staff met jointly with 

experts from academia, industry, and government, and reviewed multiple reports from leading 

AI experts. 

Through these efforts, several points became evident. First, AI is an immature 

technology; its abilities in many areas are still relatively new. Second, the workforce is affected 

by AI; whether that effect is positive, negative, or neutral remains to be seen. Third, AI requires

massive amounts of data, which may invade privacy or perpetuate bias, even when using data for 

good purposes. Finally, AI has the potential to disrupt every sector of society in both anticipated 

and unanticipated ways. In light of that potential for disruption, it’s critical that the federal 

government address the different challenges posed by AI, including its current and future 

applications. The following paper presents lessons learned from the Subcommittee’s oversight 

and hearings on AI and sets forth recommendations for moving forward.

Underlying these recommendations is the recognition the United States cannot maintain 

its global leadership in AI absent political leadership from Congress and the Executive Branch. 

Therefore, the Subcommittee recommends increased engagement on AI by Congress and the 

Administration.

Chief among the Subcommittee’s recommendations is for the federal government to 

increase federal spending on research and development to maintain American leadership with 

respect to AI. In response to concerns about AI’s potential economic impact, federal, state, and 

local agencies are encouraged to engage more with stakeholders on the development of effective 

strategies for improving the education, training, and reskilling of American workers to be more 

competitive in an AI-driven economy. The Subcommittee further recommends the federal 

government lead by example by investing more in education and training programs that would 

allow for its current and future workforce to gain necessary AI skills.

In response to concerns about privacy, the Subcommittee recommends federal agencies 

review federal privacy laws and regulations to determine how they may already apply to AI 

technologies within their jurisdiction, and, where necessary, update existing regulations to 

account for the addition of AI. To account for potential biases in AI systems, federal, state, and 

local agencies that use AI systems to make consequential decisions about people should ensure 

that the algorithms that support these systems are accountable and inspectable. 

Finally, any regulatory approach to AI should consider whether the risks to public safety 

or consumers already fall within any existing regulatory frameworks and, if so, whether those 

existing frameworks can adequately address the risks. Where a risk falls outside an existing 

regulatory framework, an approach should consider whether modifications or additions are 

needed to better account for the addition of AI.
2

As AI technology continues to advance, its progress has the potential to dramatically 

reshape the nation’s economic growth and welfare. It is critical the federal government build 

upon, and increase, its capacity to understand, develop, and manage the risks associated with this

technology’s increased use.
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INTRODUCTION

Defining AI

This paper defines AI as computational technology that works and reacts in humanlike 

ways. AI generally falls into two categories: “narrow AI” and “general AI.” Narrow AI addresses 

or solves specific tasks, “such as playing strategic games, language translation, self-driving 

vehicles, and image recognition.”1 General AI, on the other hand, can accomplish more than one 

task and can move between these tasks based on reasoning.2 Witnesses who testified before the 

Subcommittee suggested that while narrow AI is commonly utilized today, “more general 

systems . . . that can work across multiple tasks” are underdeveloped at this time.3 The examples 

of AI that are referred to in this paper concern the field of narrow AI.

Brief Background on AI

The idea of AI first emerged in 1950 with “Computing Machinery and Intelligence,”

Alan Turing’s seminal paper addressing the question of whether machines can think.

4 Turing’s 

paper also set forth a test for answering this question, and highlighted the issue of whether 

machines could be developed to learn from experiences similar to the way people do.5 The term 

“artificial intelligence” was later coined in 1956 by John McCarthy after holding the first 

academic conference on the topic.6 The last ten years have seen the most significant 

developments in AI, largely due to advancements in computing power and increased access to 

data.

Current Uses of AI

While AI is most closely associated with Silicon Valley and Hollywood, various

industries have already deployed the technology. For example, AI is now used in connection 

 1 EXECUTIVE OFFICE OF THE PRESIDENT, NATIONAL SCIENCE AND TECHNOLOGY COUNCIL COMMITTEE ON 

TECHNOLOGY, Preparing for the Future of Artificial Intelligence, (Oct. 2016), online at 

https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_

future_of_ai.pdf. see also GOVERNMENT ACCOUNTABILITY OFFICE, Artificial Intelligence: Emerging Opportunities, 

Challenges, and Implications (GAO-18-142S) (March 2018), online at https://www.gao.gov/assets/700/690910.pdf. 2 Id.

3 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the H. 

Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Oren Etzioni, CEO, Allen Institute 

for Artificial Intelligence)

4 Alan M. Turing, Computing Machinery and Intelligence, 49 Mind 433-460 (1950), online at 

https://www.csee.umbc.edu/courses/471/papers/turing.pdf (last accessed Sept. 14, 2018). 5 Id.

6 Gil Press, Artificial Intelligence Defined as a New Research Discipline: This Week in Tech History, FORBES (Aug. 

28, 2016) online at https://www.forbes.com/sites/gilpress/2016/08/28/artificial-intelligence-defined-as-a-newresearch-discipline-this-week-in-tech-history/#6913216e6dd1.
4

with mapping applications or “apps” on mobile phones,7 tax preparation,8 song writing,

9 and 

digital advertising.

10 It is also being used in video games and movies to create special effects.11

More recently, the Food and Drug Administration approved an AI algorithm that aids 

radiologists in detecting wrist fractures.12 The State of Ohio uses robotics in the Bureau of 

Criminal Investigation laboratories to help reduce the turnaround time on untested rape kits.13

The application of AI facilitated the state testing 14,000 previously untested rape kits and 

identifying 300 serial rapists linked to 1,100 crimes.14

While today’s AI products and applications are largely limited to solving specific, 

discrete tasks, because of its current and potential benefits, AI has generated broad interest across 

the economy, and as a result, will likely be a key driver of future economic growth and progress.

IMPORTANCE OF U.S. LEADERSHIP IN AI

The United States has traditionally led the world in the development and application of 

AI-driven technologies.15 This is due in part to the government’s prior commitment to investing 

heavily in research and development (R&D) that has, in turn, helped support AI’s growth and 

development. In 2015, for example, the United States led the world in total gross domestic R&D 

expenditures, spending $497 billion.16

The Subcommittee’s hearings, however, highlighted the fact that the United States’

leadership in AI is no longer guaranteed. During the hearings, several of the witnesses testified 

 7 Nick Statt, AI is Google’s secret weapon for remaking its oldest and most popular apps, THE VERGE (May 10, 

2018), online at https://www.theverge.com/2018/5/10/17340004/google-ai-maps-news-secret-weapon-remakingold-apps-products-io-2018. 8 Adelyn Zhou, EY, Deloitte, and PwC Embrace Artificial Intelligence For Tax and Accounting, FORBES (Nov. 14, 

2017), online at https://www.forbes.com/sites/adelynzhou/2017/11/14/ey-deloitte-and-pwc-embrace-artificialintelligence-for-tax-and-accounting/#2ad76d253498. 9 Matt Jancer, More Artists are Writing Songs in the Key of AI, WIRED (May 17, 2018), online at

https://www.wired.com/story/music-written-by-artificial-intelligence/. 10 Tom Simonite, Google and Microsoft Can Use AI to Extract Many More Ad Dollars from Our Clicks, FORBES

(Aug. 31, 2017), online at https://www.wired.com/story/big-tech-can-use-ai-to-extract-many-more-ad-dollars-fromour-clicks/. 11 Cade Metz, Lights, Camera, Artificial Action: Start-Up is Taking A.I. to the Movies, NEW YORK TIMES (March 

26, 2018), online at https://www.nytimes.com/2018/03/26/technology/artificial-intelligence-hollywood.html. 12 FOOD AND DRUG ADMINISTRATION, FDA permits marketing of artificial intelligence algorithm for aiding 

providers in detecting wrist fractures (May 24, 2018), online at 

https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm608833.htm. 13 OHIO OFFICE OF THE ATTORNEY GENERAL, Law Enforcement, Bureau of Criminal Investigations, Laboratory 

Division, (online at https://www.ohioattorneygeneral.gov/Law-Enforcement/Bureau-of-CriminalInvestigation/Laboratory-Division), (last visited August 22, 2018). 14 Anna Boiko-Weyrauch, Her Rapist was Convicted because of a Rape Kit. So Why are So Many Untested?, 

KUOW (August 15, 2018) online at http://kuow.drupal.publicbroadcasting.net/post/her-rapist-was-convictedbecause-rape-kit-so-why-are-so-many-kits-untested. 15 McKinsey Global Institute, Artificial Intelligence: Implications for China (April 2017) online at

https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/China/Artificial%20intelligence%20Implicati

ons%20for%20China/MGI-Artificial-intelligence-implications-for-China.ashx. 16 NATIONAL SCIENCE BOARD, 2018 SCIENCE & ENGINEERING INDICATORS (2018), online at

www.nsf.gov/statistics/2018/nsb20181/assets/nsb20181.pdf.
5

the United States needs to increase its R&D spending to remain competitive in the field of AI. 

One witness stated, “[w]hile other governments are aggressively raising their research funding, 

U.S. government research has been relatively flat.”17

Another witness expressly warned, “[c]urrent federal funding levels are not keeping pace 

with the rest of the industrialized world.”18

Notably, China’s commitment to 

funding R&D has been growing sharply, 

up 200 percent from 2000 to 2015.

19 On 

February 7, 2018, the National Science 

Board’s (Board) and the National 

Science Foundation’s (NSF) Director, 

who jointly head NSF, said in a 

statement that if current trends continue, 

the Board expects “China to pass the 

United States in R&D investments” by 

the end of 2018.20

Recent progress was made when 

the Defense Advanced Research Projects 

Agency (DARPA) announced the 

creation of the Artificial Intelligence 

Exploration program, “AI Next,” to 

bolster the United States’ leadership in 

AI. DARPA plans to invest more than $2 

billion into this program and other

existing programs. The program focuses 

research on “‘third wave’ AI theory and 

application that will make it possible for 

machines to contextually adapt to changing situations.”21

 17 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Ian Buck, Vice President and 

General Manager, Tesla Data Center Business, NVIDIA). 18 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Amir Khosrowshahi, Vice 

President and Chief Technology Officer, Artificial Intelligence Group, Intel Corp.). 19 NATIONAL SCIENCE BOARD, 2018 SCIENCE & ENGINEERING INDICATORS (online at

www.nsf.gov/statistics/2018/nsb20181/assets/nsb20181.pdf).

20 NATIONAL SCIENCE FOUNDATION, NATIONAL SCIENCE BOARD STATEMENT ON GLOBAL RESEARCH AND 

DEVELOPMENT (R&D) INVESTMENTS NSB-2018-9 (Feb. 7, 2018), online at

www.nsf.gov/nsb/news/news_summ.jsp?cntn_id=244465 (last accessed September 17, 2018). 21 Defense Advanced Research Projects Agency, DARPA Announces $2 Billion Campaign to Develop Next Wave of 

AI Technologies (Sept. 7, 2018), online at https://www.darpa.mil/news-events/2018-09-07.
6

The chart on the previous page shows China’s rapidly growing investment in AI. 

Particularly concerning is the prospect of an authoritarian country, such as Russia or China, 

overtaking the United States in AI. As the Subcommittee’s hearings showed, AI is likely to have 

a significant impact in cybersecurity, and American competitiveness in AI will be critical to 

ensuring the United States does not lose any decisive cybersecurity advantage to other nationstates.22

The loss of American leadership in AI could also pose a risk to ensuring any potential use 

of AI in weapons systems by nation-states comports with international humanitarian laws. In 

general, authoritarian regimes like Russia and China have not been focused on the ethical 

implications of AI in warfare, and will likely not have guidelines against more bellicose uses of

AI, such as in autonomous weapons systems.23

The United States’ competitiveness in AI is also critical to its economic security, as AI is 

poised to be a key driver of economic growth. AI applications promise to make industry more 

efficient—cutting down costs, limiting the use of natural resources, and improving the use of 

finite resources such as “the increasingly crowded electromagnetic spectrum.”24

For example, the General Services Administration has a robotic processing automation 

(RPA) pilot that automates portions of the Multiple Award Schedules new offer review process. 

Presently, contract officers must go through a tedious administrative process, reading through 

dozens of pages of documentation across multiple IT systems to ensure a vendor’s new offer is 

consistent with information already in government databases. RPA software offers the capability 

to perform these tasks, so the contract officers can spend more time engaging with customers.25

In an effort to keep the United States at the forefront of AI developments and 

advancements, the Obama Administration released three reports in 2016 that assessed the state of 

AI. The reports focused on the public policy questions AI raises for the country, and proposed a 

series of recommendations.26 The current Administration should prioritize building on these 

 22 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Ben Buchanan, Postdoctoral Fellow, Belfer Center Cyber Security Project, Science, Technology, and 

Public Policy Program, Harvard University). Dr. Buchanan currently serves as an Assistant Teaching Professor at 

Georgetown University’s School of Foreign Service. 

23 CENTER FOR A NEW AMERICAN SECURITY, Autonomous Weapons (online at 

https://www.cnas.org/research/technology-and-national-security/autonomous-weapons) (accessed June 19, 2018).

24 Spectrum Collaboration Challenge, What is the Spectrum Collaboration Challenge? DEFENSE ADVANCED 

RESEARCH PROJECTS AGENCY, (available at https://spectrumcollaborationchallenge.com/about/) (accessed Aug. 15, 

2018).

25 Game Changers: Artificial Intelligence Part II, Artificial Intelligence and the Federal Government: Hearing 

Before the Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th

Cong. (2018) (statement of Mr. Keith Nakasone, Deputy Assistant Commissioner Category Acquisition 

Management, U.S. General Services Administration).

26 EXECUTIVE OFFICE OF THE PRESIDENT, NATIONAL SCIENCE AND TECHNOLOGY COUNCIL COMMITTEE ON 

TECHNOLOGY, Preparing for the Future of Artificial Intelligence, (Oct. 2016), online at 

https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_

future_of_ai.pdf; EXECUTIVE OFFICE OF THE PRESIDENT, NATIONAL SCIENCE AND TECHNOLOGY COUNCIL

COMMITTEE ON TECHNOLOGY, NETWORKING AND INFORMATION TECHNOLOGY RESEARCH AND DEVELOPMENT 
7

efforts and ensure federal agencies are implementing these recommendations. Recent efforts by 

the Trump Administration recognize AI’s growing importance. In particular, the Administration 

has highlighted AI in the 2017 National Security Strategy, 2018 Summary of the National 

Defense Strategy, the Office of Management and Budget (OMB) and Office of Science and 

Technology Policy’s (OSTP) FY2019 Administration Research and Development Budget 

Priorities, and the FY2019 Budget Request. OSTP also held a summit on the topic in May 2018, 

and established the National Science and Technology Council Select Committee on AI.

27

As the United States considers the impact of AI in both foreign and economic affairs, we

must keep in mind that American values—the right to privacy, free speech, the rule of law, and 

respect for intellectual property—give America many intangible advantages over other nations.

As Subcommittee Chairman Hurd said in June, “the United States boasts a creative, risk-taking 

culture that is inextricably linked to its free enterprise system.”28 Gary Shapiro testified before 

the Subcommittee, “[the United States’] competitive strength is innovation.”29 Throughout the 

hearings, witnesses repeatedly acknowledged these advantages are important components driving 

American leadership in AI’s development and deployment. We cannot presume that these values 

will automatically secure our leadership, but we should be aware of them and regard them as 

strengths.

AI’S CHALLENGES

The Subcommittee’s hearings showed AI faces a number of different challenges. In this 

paper, we will address the four challenges discussed during the hearings—workforce, privacy, 

bias, and malicious use of AI. 

Workforce

One of the central concerns raised during the hearings is that AI advancement in the 

short-term could lead to the loss of jobs due to AI-driven automation.

30 A December 2017 report 

from the McKinsey Global Institute reported that as a result of AI-driven automation, “up to 1/3 

 

SUBCOMMITTEE, The National Artificial Intelligence Research and Development Strategic Plan (Oct. 2016) online 

at

https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/national_ai_rd_stra

tegic_plan.pdf; EXECUTIVE OFFICE OF THE PRESIDENT, Artificial Intelligence, Automation, and the Economy (Dec. 

2016) online at https://obamawhitehouse.archives.gov/sites/whitehouse.gov/files/documents/Artificial-IntelligenceAutomation-Economy.PDF. 27 EXECUTIVE OFFICE OF THE PRESIDENT, OFFICE OF SCIENCE AND TECHNOLOGY POLICY, SUMMARY OF THE 2018

WHITE HOUSE SUMMIT ON ARTIFICIAL INTELLIGENCE FOR AMERICAN INDUSTRY (2018), online at

https://www.whitehouse.gov/wp-content/uploads/2018/05/Summary-Report-of-White-House-AI-Summit.pdf. 28 Will Hurd, Washington Needs to Adopt AI soon or We’ll Lose Millions, FORTUNE, (June 12, 2018), online at 

http://fortune.com/2018/06/12/rep-will-hurd-artificial-intelligence/. 29 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Mr. Gary Shapiro, CEO of the Consumer Technology Association). 30 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Ben Buchanan, Postdoctoral Fellow, Belfer Center Cyber Security Project, Science, Technology, and 

Public Policy Program, Harvard University).
8

of [the] workforce in the United States and Germany may need to find work in new 

occupations.”31

Another study released by Oxford University in 2013 found the impact on U.S. workers 

by AI technologies may even be higher. According to the Oxford study, “about 47 percent of 

total U.S. employment is at risk.”32 These studies indicate the negative impact AI may have on 

jobs, which has the potential to increase wealth inequality in the United States.

Some of the hearing witnesses and other studies, however, show AI has the capacity to 

improve and increase jobs.33 For example, the Organisation for Economic Co-operation and 

Development (OECD) released a study in March 2018 finding that about fourteen percent of jobs 

in OECD countries have a high risk of automation.34 Additionally, a Deloitte study of 140 years 

of census data in the United Kingdom examined the effect of new technologies on jobs, and 

found in spite of new technologies, more jobs were ultimately created than eliminated.35

The common thread from all of these studies is that our economic policies must take into 

account the uncertain future of work faced by Americans as AI takes hold, and the need for 

increased investments in education and worker retraining. As such, federal, state, and local 

agencies should be encouraged to engage more with educators, employers, employees, unions, 

and other stakeholders on the development of effective strategies for improving the education, 

training, and reskilling of American workers to be more competitive in an AI-driven economy. 

The federal government should also lead by example by investing more in education and training 

programs that would allow for its current and future workforce to gain the necessary AI skills.

Privacy

AI technologies rely on computer algorithms that use data to determine how they will 

respond to new inputs.36 Since AI requires vast amounts of data, witnesses in the

Subcommittee’s hearings frequently cited individuals’ privacy as a potential challenge. For 

 31 McKinsey Global Institute, Jobs Lost, Jobs Gained: Workforce Transitions In a Time of Automation (Dec. 2017),

online at

www.mckinsey.com/~/media/McKinsey/Global%20Themes/Future%20of%20Organizations/What%20the%20futur

e%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-GainedReport-December-6-2017.ashx. 32 CARL BENEDIKT FREY & MICHAEL A. OSBORNE, The Future of Employment: How Susceptible are Jobs to 

Computerization?, Comment, Uni. Oxford, (Sept. 17, 2013), online at 

www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf.

33 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Mr. Gary Shapiro, CEO of the Consumer Technology Association).

34 Organisation for Economic Co-operation and Development, Putting faces to the jobs at risk of automation,

POLICY BRIEF ON THE FUTURE OF WORK, (March 2018), online at https://www.oecd.org/employment/Automationpolicy-brief-2018.pdf. 35 IAN STEWART, DEBAPRATIM DE, & ALEX COLE. Technology and People: The Great Job-Creating Machine,

Deloitte (August 2015), online at https://www2.deloitte.com/uk/en/pages/finance/articles/technology-andpeople.html (last accessed September 14, 2018). 36 Tom Simonite, The Wired Guide to Artificial Intelligence, WIRED (Feb. 1, 2018), online at 

www.wired.com/story/guide-artificial-intelligence/.
9

example, Dr. Ben Buchanan, an AI expert, testified about the various privacy risks consumers 

face when their personal data is used in AI systems.37 According to Dr. Buchanan, “[t]here is the 

risk of breaches by hackers, of misuse by those who collect it or access it, and of secondary 

use—in which data collected for one purpose is later re-appropriated for another.”38

These fears were realized when one of the nation’s largest credit reporting agencies, 

Equifax, Inc., announced in 2017 that hackers had successfully penetrated its systems, and 

gained access to the personal data of approximately 145.5 million Americans.39 The data 

compromised included sensitive information Equifax had collected on consumers ranging from 

“Social Security numbers, birth dates, addresses, and in some instances, driver’s license 

numbers.”40

Other examples where privacy concerns are implicated is the use of smart speakers that 

often feature voice-activated digital assistants. For instance, if a smart speaker is always listening 

in order to respond to a command, what is done with the hours of data it overhears? Law 

enforcement has already begun requesting voice recordings from technology companies for 

criminal cases. This raises the question of how devices that are always listening could potentially 

be used as evidence against consumers.

41

To address the different privacy challenges raised by AI-driven technologies, one 

witness, Dr. Buchanan, testified before the Subcommittee that companies need to adopt more 

stringent safeguards in the design and development of their AI systems.42 However, other 

witnesses, such as Dr. Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence43 and 

 37 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Ben Buchanan, Postdoctoral Fellow, Belfer Center Cyber Security Project, Science, Technology, and 

Public Policy Program, Harvard University).

38 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Ben Buchanan, Postdoctoral Fellow, Belfer Center Cyber Security Project, Science, Technology, and 

Public Policy Program, Harvard University).

39 Equifax, Equifax Announces Cybersecurity Firm Has Concluded Forensic Investigation of Cybersecurity 

Incident: Potentially Impacted U.S. Consumers Increased by 2.5 Million (Oct. 2, 2017), online at 

https://investor.equifax.com/news-and-events/news/2017/10-02-2017-213238821; Equifax, Equifax Announces 

Cybersecurity Incident Involving Consumer Information (Sept. 7, 2017), online at 

https://investor.equifax.com/news-and-events/news/2017/09-07-2017-213000628. 40 Equifax, Equifax Announces Cybersecurity Incident Involving Consumer Information (Sept. 7, 2017), online at 

https://investor.equifax.com/news-and-events/news/2017/09-07-2017-213000628. 41 Jeff John Roberts, Police Ask Amazon’s Echo to Help Solve a Murder, FORTUNE (Dec. 27, 2016), online at

http://fortune.com/2016/12/27/amazon-echo-murder/. 42 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Ben Buchanan, Postdoctoral Fellow, Belfer Center Cyber Security Project, Science, Technology, and 

Public Policy Program, Harvard University). 43 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Oren Etzioni, CEO, Allen 

Institute for Artificial Intelligence)
10

Gary Shapiro, President of the Consumer Technology Association, 44 argued that rather than 

trying to regulate all AI-related privacy issues under one umbrella, regulations should be tailored 

to individual AI applications. Some AI products and applications may already be subject to 

federal privacy laws, such as the Health Insurance Portability and Accountability Act, Children’s 

Online Privacy Protection Act, Gramm-Leach-Bliley Act, or fall under the jurisdiction of the 

Federal Trade Commission, the primary federal privacy regulator.

45

The growing collection and use of personal data in AI systems and applications raises 

legitimate concerns about privacy. As such, federal agencies should review federal privacy laws, 

regulations, and judicial decisions to determine how they may already apply to AI products 

within their jurisdiction, and—where necessary—update existing regulations to account for the 

addition of AI.

Biases

The increasing reliance on AI to make consequential decisions about individuals has also 

heightened concerns about the technology’s accuracy, particularly when used by governments. 

As the Electronic Privacy Information Center (EPIC) explained in a statement to the 

Subcommittee: “[w]hen the government uses AI to make decisions about people, it raises 

fundamental questions about accountability, due process, and fairness.”46

At its core, AI is reliant upon data. If the data itself is incomplete, biased, or skewed in 

some other fashion, the AI system is at risk of being inaccurate.

47 As AI systems rely upon larger 

and larger quantities of data, the risk increases that the data sets may knowingly or unknowingly 

contain biases. There are legitimate concerns that if an AI system is trained on biased data, the 

AI system will produce biased results.48

For example, in 2016, ProPublica began to investigate the use of computerized “risk 

prediction” tools by some judges in criminal sentencing and bail hearings. The investigation 

 44 Game Changers: Artificial Intelligence Part II1, Artificial Intelligence and Public Policy: Hearing Before the 

Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th Cong. (2018) 

(statement of Mr. Gary Shapiro, CEO of the Consumer Technology Association). 45 See Health Insurance Portability and Accountability Act of 1996, Pub. L. No. 104-191, 110 Stat. 1936, (1996) 

(codified at 42 U.S.C. § 300gg and 29 U.S.C. § 1181 et seq. and 42 U.S.C. 1320d et seq.); Children’s Online 

Privacy Protection Act of 1998, Pub. L. No. 105-277, 112 Stat. 2681-728, (2000) (codified at 15 U.S.C. §§ 6501–

6506); Federal Services Modernization Act of 1999 (Gramm-Leach-Bliley Act), Pub. L. No. 106-102, 113 Stat. 

1338, (1999) (codified at 15 U.S.C. §§6801-6809; §§ 6821-6827 and at 12 U.S.C. §1831u et seq.). 46 Letter from Electronic Privacy Information Center to Rep. William Hurd, Chairman, Subcommittee on 

Information Technology, House Oversight and Government Reform Committee, and Rep. Robin Kelly, Ranking 

Member, Subcommittee on Information Technology, House Oversight and Government Reform Committee (April 

19, 2018) (online at https://www.epic.org/testimony/congress/EPIC-HCOGR-AI-Apr2018.pdf). 47 Tom Simonite, The Wired Guide to Artificial Intelligence, Wired (Feb. 1, 2018), online at

www.wired.com/story/guide-artificial-intelligence/; National Science and Technology Council, Preparing for the 

Future of Artificial Intelligence (Oct. 2016) (online at

obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_

of_ai.pdf).

48 Forget Killer Robots – Bias is the Real AI Danger, MIT TECHNOLOGY REVIEW (Oct. 3, 2017), online at

https://www.technologyreview.com/s/608986/forget-killer-robotsbias-is-the-real-ai-danger/.
11

found the algorithm the systems relied upon was racially biased and inaccurate.49 In total, 

African-Americans were “almost twice as likely as whites to be labeled a higher risk,” despite 

the fact those African-Americans who had been labeled high risk were subsequently found to not 

go on to commit another crime.50 As AI technology is increasingly deployed into industries such 

as finance, law, and medicine, these biases could be reinforced by the technology, and harm 

populations.

During the Subcommittee’s hearings, witnesses and other stakeholders also made clear 

one of the most effective ways in which bias or potential biases in AI systems can be addressed 

is by increasing transparency in the use of these systems. As Dr. Charles Isbell explained in his 

testimony:

An AI system should [be] inspectable. The kind of data the 

algorithm uses to build its model should be available. The decisions 

that such algorithms make should be inspectable. In other words, as 

we deploy these algorithms, each algorithm should be able to 

explain its output.51

The solutions to addressing bias in AI are also cross-cutting. For example, Accenture 

recently introduced an “AI fairness tool,” which uses AI to examine how data influences 

variables, such as age, gender, and race in a model.52 Civil society groups, such as the 

Partnership on AI and the AI Now Institute, are also researching and engaging in discussions 

around bias and AI.53

In short, addressing biases and potential biases in AI systems will necessitate 

improvements in transparency when those systems are used to make consequential decisions 

about individuals. 

Federal, state, and local agencies that use AI-type systems to make consequential 

decisions about people should ensure the algorithms supporting these systems are accountable 

and inspectable. In addition, federal, state, and local governments are encouraged to more 

actively engage with academic institutions, non-profit organizations, and the private sector in 

discussions on how to identify bias in the use of AI systems, how best to eliminate bias through 

technology, and how to account for bias.

 49 Julia Angwin et al., Machine Bias, PROPUBLICA (May 23, 2016), online at www.propublica.org/article/machinebias-risk-assessments-in-criminal-sentencing. 50 Id. 51 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Dr. Charles Isbell, Senior 

Associate Dean, College of Computing, Georgia Institute of Technology). 52 Natasha Lomas, Accenture Wants to Beat Unfair AI with a Professional Toolkit, TECHCRUNCH (June 9, 2018), 

online at https://techcrunch.com/2018/06/09/accenture-wants-to-beat-unfair-ai-with-a-professional-toolkit/.

53AI NOW INSTITUTE, https://ainowinstitute.org (accessed on Aug. 23, 2018); PARTNERSHIP ON AI, 

https://partnershiponai.org (accessed on Aug. 23, 2018).
12

Malicious Use of AI

The Subcommittee’s hearings also highlighted the need to prepare for and protect against 

the malicious use of AI. Earlier this year, OpenAI, a non-profit AI research company that 

testified at one of the hearings, co-authored a report finding that unless adequate defenses are 

developed, AI progress will result in cyberattacks that are “more effective, more finely targeted, 

more difficult to attribute, and more likely to exploit vulnerabilities in AI systems.”54 The 

report’s findings are consistent with those from a 2017 survey conducted by the cybersecurity 

firm Cylance. According to the Cylance survey, “62 percent of [information security] experts 

believe artificial intelligence will be used for cyberattacks in the coming year.”55

AI’s computing power enables it to increase the severity of cyberattacks exponentially. 

Three areas of malicious AI merit particular attention: political security; physical security; and 

digital security.56 The common theme between these three spheres is AI expands the level of 

risk. For example, cyberattacks can affect more devices, people, and companies in a single 

moment, undermining digital security. In fact, the United States has begun to see cyberattacks 

against it using AI.57

Consider the Russian disinformation campaigns of the past few years. With AI, “fake 

news” can be exponentially more convincing, with the potential to create videos of people 

making statements that they never made—known as “deepfakes”—as featured on Radiolab’s 

Breaking News episode last summer.58 AI, using data, can pinpoint those who are most 

susceptible to disinformation with little human effort. This capability has the potential to greatly 

expand the number of people impacted in any disinformation campaign employed by hostile 

nation-states to disrupt another state’s political system.

Physical security can also be compromised by AI systems. For example, a team of 

researchers from American universities showed how autonomous vehicles could be tricked by 

hackers into misinterpreting stop signs with a few simple stickers that would otherwise appear 

innocuous.59

As we consider all the positive ways AI will be used in the future, the government must 

also consider the ways it could be used to harm individuals and society and prepare for how to 

mitigate these harms.

 54 Miles Brundage, et al., The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation, 

(2018), online at https://www.eff.org/files/2018/02/20/malicious_ai_report_final.pdf 55 Cylance, Black Hat Attendees See AI as Double-Edged Sword, THREATMATRIX (Aug. 1, 2017), online at

threatmatrix.cylance.com/en_us/home/black-hat-attendees-see-ai-as-double-edged-sword.html. 56 Miles Brundage, et al., The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation, 

(2018), available at https://www.eff.org/files/2018/02/20/malicious_ai_report_final.pdf. 57 The Morning Download: First AI-Powered Cyberattacks are Detected, WALL STREET JOURNAL (Nov. 16, 2017), 

online at https://blogs.wsj.com/cio/2017/11/16/the-morning-download-first-ai-powered-cyberattacks-are-detected/. 58 RadioLab: Breaking News, WNYC STUDIOS (July 27, 2017), online at 

https://www.wnycstudios.org/story/breaking-news/.

59 David Z. Morris, Researchers Show How Simple Stickers Could Trick Self-Driving Cars, FORTUNE (Sep. 2, 2017),

online at http://fortune.com/2017/09/02/researchers-show-how-simple-stickers-could-trick-self-driving-cars/.
13

How should the government respond to AI?

The U.S. government has traditionally taken a hands-off approach to emerging

technologies. During the 1990s, the government’s preferred policy when it came to the internet 

was to favor private action over public regulation. During that period, although Congress and 

state legislatures passed several laws governing commerce, content, and competition, they 

generally focused on crafting legal superstructures for the emerging web, not micromanaging its 

development; examples include the Internet Tax Freedom Act60 and the Telecommunications Act 

of 1996.

61 Concurrently, the Clinton Administration adopted a policy of salutary neglect. 

President Clinton ordered his administration to “do nothing that undermines the capacity of 

emerging technologies to lift the lives of ordinary Americans.”62

It is the Subcommittee’s recommendation that the federal government should approach 

any potential regulation of AI with the above history in mind. The government should begin by 

first assessing whether the risks to public safety or consumers already fall within existing 

regulatory frameworks and, if so, consideration should be made as to whether those existing 

frameworks can adequately address the risks. If those risks fall outside the existing regulatory 

framework, an approach should consider carefully whether modifications or additions are needed 

to better account for the addition of AI. 

At minimum, a widely agreed upon standard for measuring the safety and security of AI

products and applications should precede any new regulations. A common taxonomy also would

help facilitate clarity and enable accurate accounting of skills and uses of AI. The National 

Institute of Standards and Technology (NIST) is situated to be a key player in developing 

standards. Similar private sector efforts exist from the Institute of Electrical and Electronics 

Engineers’ Global Initiative on Ethics of Autonomous and Intelligent Systems.

63 The AI Index,

which is a part of Stanford’s “One Hundred Year Study on AI,” collects data about AI in order to 

track and measure its progress, which will be critical in the standards development process to 

provide historical context. 64 The federal government should look to support public, academic,

and private sector efforts in the development of standards for measuring the safety and security 

of AI products and applications.

There are also tangible ways for the federal government to facilitate greater AI 

innovation absent regulation. For one, the government holds thousands of different data sets that 

could be useful to researchers studying AI and to agencies in accomplishing their missions. 

Many of these data sets are a public good and should be accessible to the public. 

 60 Internet Tax Freedom Act of 1998, Pub. L. No. 105-277, 112 Stat. 2681–719 (amending 15 U.S.C. § 151) (1998). 61 Telecommunications Act of 1996, Pub. L. No. 104-104, 110 Stat. 56, (codified as § 47 U.S.C. 151 et, seq. (1996). 62 Bill Clinton, President, and Al Gore, Vice President, Remarks by the President at and the Vice President at 

Electronic Commerce Event, (Nov. 30, 1998) (online at 

https://govinfo.library.unt.edu/npr/library/speeches/rmkselec.html) (last accessed September 17, 2018). 63 IEEE Standards Association, The IEEE Global Initiative on Ethics and Autonomous and Intelligent Systems, 

(online at https://standards.ieee.org/develop/indconn/ec/autonomous_systems.html) (accessed on July 17, 2018). 64 Artificial Intelligence Index, Our Mission, (online at http://aiindex.org/#mission) (accessed on July 17, 2018).
14

As such, the Senate should work to pass the OPEN Government Data Act (OGDA), 

which the House passed unanimously last year.65 OGDA would allow for all non-sensitive 

government data to be made freely available and accessible to the public.66 During the 

Subcommittee’s hearings, several witnesses testified AI’s development would be enhanced by 

more open data policies.67 Provided the Senate passes OGDA, the President should sign it into 

law and the Administration should implement it as quickly as possible.

The Subcommittee also sees great value in encouraging innovation through national 

competitions. There should be a Grand Challenge, similar to DARPA’s Grand Challenges, using 

data to solve a problem. The benefit of DARPA’s Grand Challenges is their ability to foster 

innovative, collaborative research among teams seeking to overcome seemingly unattainable 

goals. Take, for example, DARPA’s Self-Driving Car Challenge, which offered $1 million to the 

first team to autonomously navigate a desert course from California to Nevada. In the first year 

of the Challenge, no team completed the course. In fact, the farthest any vehicle went was 7.5 

miles. Yet eighteen months later, 5 out of the 195 competing teams completed the 132-mile 

course, with the winner having crossed the finish line in a little under seven hours.

68 DARPA’s

Grand Challenges provide strong incentives for innovation, and, as seen with its Self-Driving 

Cars Challenge, can effectuate quick technological advancement. Such competitions have 

spurred creativity, research, and collaboration, leading to some of the most groundbreaking 

inventions in recent history.

Another recommendation universally supported by witnesses at the hearings was a need 

for more financial support for R&D. The Subcommittee is encouraged by the research already 

occurring at universities and not-for-profits, as well as commercial R&D. The aggregate work of 

these bodies is why the United States is a leader in AI.

However, to maintain American leadership there is a need for increased funding for R&D

at agencies like the National Science Foundation, National Institutes of Health, Defense 

Advanced Research Project Agency, Intelligence Advanced Research Project Agency, National 

Institute of Standards and Technology, Department of Homeland Security, and National 

Aeronautics and Space Administration. As such, the Subcommittee recommends the federal 

government provide for a steady increase in federal R&D spending. An additional benefit of 

increased funding is being able to support more graduate students, which could serve to expand 

the future workforce in AI. 

 65 Foundations for Evidence-Based Policymaking Act, H.R. 4174, §201-202, 115th Cong. (1st Sess. 2017). 66 Open, Public, Electronic, and Necessary (OPEN) Government Data Act, H.R. 1770, S. 760, 115th Cong. (1st Sess. 

2017).

67 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018) (statement of Ian Buck, Vice President and 

General Manager, Tesla Data Center Business, NVIDIA); Game Changers: Artificial Intelligence Part 1: Hearing 

Before the Subcomm. on Information Technology of the H. Comm. on Oversight and Government Reform, 115th

Cong. (2018) (statement of Amir Khosrowshahi, Vice President and Chief Technology Officer, Artificial 

Intelligence Group, Intel Corp.). 68 Defense Advanced Research Projects Agency, The DARPA Grand Challenge: Ten Years Later (March 13, 2014), 

online at https://www.darpa.mil/news-events/2014-03-13 (last accessed on September 17, 2018).
15

CONCLUSION

AI has implications for every sector of industry and each Congressional committee 

should examine the role AI will play within their jurisdictions. To date, there have been six

hearings held on AI: three by this Subcommittee; two by the Senate Committee on Commerce, 

Science and Transportation in 2016 and 2017; and one by the House Science, Space and 

Technology Committee in June 2018.

69 More oversight action by Congress is needed.

There is also a pressing need for conscious, direct, and spirited leadership from the 

Trump Administration. The 2016 reports put out by the Obama Administration’s National 

Science and Technology Council and the recent actions of the Trump Administration are steps in 

the right direction. However, given the actions taken by other countries—especially China—

Congress and the Administration will need to increase the time, attention, and level of resources 

the federal government devotes to AI research and development, as well as push for agencies to 

further build their capacities for adapting to advanced technologies.

The government has an essential role to play in securing American leadership in AI. 

Fulfilling this role will require balancing the creative energy of innovative Americans whose 

knowledge and entrepreneurial spirit have driven the development of this technology with 

regulatory frameworks that protect consumers. To ensure the appropriate balance is met, it is 

vital Congress and the Executive Branch continue to educate themselves about AI, increase the 

expenditures of R&D funds, help set the agenda for public debate, and, where appropriate, define

the role of AI in the future of this nation. As our hearings have shown, these steps are necessary

for the United States to remain at the forefront of AI advancement.

 69 Game Changers: Artificial Intelligence Part 1: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018); Game Changers: Artificial Intelligence Part 

II, Artificial Intelligence and the Federal Government: Hearing Before the Subcomm. on Information Technology of 

the H. Comm. on Oversight and Government Reform, 115th Cong. (2018); Game Changers: Artificial Intelligence 

Part II1, Artificial Intelligence and Public Policy: Hearing Before the Subcomm. on Information Technology of the 

H. Comm. on Oversight and Government Reform, 115th Cong. (2018); The Dawn of Artificial Intelligence: Hearing 

Before the Subcomm. on Space, Science, and Competitiveness of the S. Comm. on Commerce, Science, & 

Transportation, 114th Cong. (2016); Digital Decision-Making: The Building Blocks of Machine Learning and 

Artificial Intelligence: Hearing Before the Subcomm. on Communications, Technology, Innovation, and the Internet 

of the S. Comm. on Commerce, Science, & Transportation, 114th Cong (2017); Artificial Intelligence – With Great 

Power Comes Great Responsibility: Hearing Before the Subcomm. on Research and Technology and Subcomm.on 

Energy the H. Comm. on Science, Space and Technology Committee, 115th Cong. (2018).