R A I L

The Journal of Robotics,

Artificial Intelligence & Law

COURT

PRESS

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R A I L

Volume 4, No. 3 | May–June 2021

Editor’s Note: Stablecoin

Victoria Prussen Spears

What 2021 Has in Store for Stablecoin

Robin Nunn, Sarah V. Riddell, and Steven Lightstone

U.S. State Department Issues Human Rights Compliance Guidance for Products and

Services with Surveillance Capabilies

Michael R. Lienberg and Anne-Marie L. Beliveau

The Impact of COVID-19 on Blockchain Advancement

Keith B. Letourneau and Vanessa DiDomenico

FAA Releases Two Final Rules to Advance Drone Integraon

Joel E. Roberson, Anita M. Mosner, Marina Veljanovska O’Brien, and Ben Slocum

NHTSA Proposes Rule on Safe Deployment of Self-Driving Vehicles

Rebecca Baden Chaney and Rukiya Mohamed

Facial Recognion, Racial Recognion, and the Clear and Present Issues with AI Bias

Daniel C. Wood

Digitalized Discriminaon: COVID-19 and the Impact of Bias in Arcial Intelligence

Michael S. Horikawa

Everything Is Not Terminator: The Federal Government and Trustworthy AI

John Frank Weaver

RAIL

The Journal of Robotics,

Artificial Intelligence & Law

Volume 4, No. 3 | May–June 2021

161 Editor’s Note: Stablecoin

Victoria Prussen Spears

165 What 2021 Has in Store for Stablecoin

Robin Nunn, Sarah V. Riddell, and Steven Lightstone

185 U.S. State Department Issues Human Rights Compliance Guidance

for Products and Services with Surveillance Capabilies

  MichaelR.LienbergandAnne-MarieL.Beliveau

199 The Impact of COVID-19 on Blockchain Advancement

  KeithB.LetourneauandVanessaDiDomenico

205 FAA Releases Two Final Rules to Advance Drone Integraon

  JoelE.Roberson,AnitaM.Mosner,MarinaVeljanovskaO’Brien,

andBenSlocum

213 NHTSA Proposes Rule on Safe Deployment of Self-Driving Vehicles

  RebeccaBadenChaneyandRukiyaMohamed

219 Facial Recognion, Racial Recognion, and the Clear and Present

Issues with AI Bias

  DanielC.Wood

223 Digitalized Discriminaon: COVID-19 and the Impact of Bias in

Arcial Intelligence

  MichaelS.Horikawa

227 Everything Is Not Terminator: The Federal Government and

Trustworthy AI

  JohnFrankWeaver

EDITOR-IN-CHIEF

Steven A. Meyerowitz

President, Meyerowitz Communications Inc.

EDITOR

Victoria Prussen Spears

Senior Vice President, Meyerowitz Communications Inc.

BOARD OF EDITORS

Miranda Cole

Partner, Covington & Burling LLP

Kathryn DeBord

Partner & Chief Innovation Ocer, Bryan Cave LLP

Melody Drummond Hansen

Partner, O’Melveny & Myers LLP

Paul B. Keller

Partner, Allen & Overy LLP

Garry G. Mathiason

Shareholder, Littler Mendelson P.C.

Elaine D. Solomon

Partner, Blank Rome LLP

Linda J. ayer

Partner, Finnegan, Henderson, Farabow, Garrett & Dunner LLP

Edward J. Walters

Chief Executive Ocer, Fastcase Inc.

John Frank Weaver

Attorney, McLane Middleton, Professional Association

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ISSN 2575-5633 (print) / ISSN 2575-5617 (online)

Everything Is Not Terminator

The Federal Government and

Trustworthy AI

John Frank Weaver*

Although President Biden has begun overturning the previous

administration’s executive orders, many of those prior orders will

survive. One such order appears to be Executive Order 13,960,

“Promoting the Use of Trustworthy Artificial Intelligence [“AI”] in

the Federal Government” (the “Order”).

The purpose of the Order

is to provide guidance to federal agencies to ensure they “design,

develop, acquire, and use AI in a manner that fosters public trust

and confidence while protecting privacy, civil rights, civil liberties

and American values.”

The Order is intended to push forward

the AI priorities of Executive Order 13,859,

which implemented

principles and objectives for federal agencies to rely on to drive

American advancements in AI, and the 2020 memo from the

Office of Management and Budget (the “OMB Memo”), which set

out policy considerations to guide regulatory and non-regulatory

approaches to AI applications developed and deployed outside the

federal government.

The Order does not provide sufficient direction regarding the

results we want federal government AI to produce, but it will have

direct and indirect effects on AI development and adoption in the

public and private sectors. Below, I outline a few of those.

Federal Principles in the Process, But No

Federal Values in the End Result

The OMB Memo provided 10 principles for federal agencies

to use when developing—or declining to develop—regulations

governing AI:

1. Promote public trust in AI;

2. Provide ample opportunities for the public to participate

in and provide feedback on rulemaking governing AI;

228 e Journal of Robotics, Articial Intelligence & Law [4:227

3. Leverage scientic and technical information and processes;

4. Assess risks in subject AI;

5. Consider the costs and benets of any AI;

6. Maintain a exible approach to adapt to changes and

updates to AI applications;

7. Consider impacts AI may have on fairness and discrimination;

8. Incorporate disclosure and transparency in the rulemak-

ing process to increase public trust and condence in AI

applications;

9. Promote AI systems that are safe, secure, and operate as

intended; and

10. Coordinate with other federal agencies on AI strategies.

The Order seeks to impose similar (although not identical)

principles on federal agencies as they design, develop, or acquire

AI applications:

■ Lawful and “respectful of our Nation’s values”;

■ Purposeful and performance-driven;

■ Accurate, reliable, and eective;

■ Safe, secure, and resilient;

■ Understandable;

■ Responsible and traceable;

■ Regularly monitored;

■ Transparent; and

■ Accountable.

In general, although the OMB Memo prioritizes innovation

and growth and the Order prioritizes building trust in the federal

government’s AI applications, both do so by requiring develop-

ment processes that balance similar, competing interests (i.e., the

principles): accuracy, safety, transparency, accountability, well-

reviewed, etc. This is done on a case-by-case basis.

The principles in the Order (and the OMB Memo) therefore

provide a checklist for AI designers and developers to measure their

application development processes against. Private companies that

provide AI services and applications to the federal government

will need to incorporate the principles into their development

cycles and be able to demonstrate them. These requirements will

likely necessitate significant research, development, and marketing

investment in order to properly appeal to the federal government

2021] e Federal Government and Trustworthy AI 229

as a customer. For companies that market AI to both Washington

and private companies, that investment is likely to influence its

development of private-sector AI as well. Depending on how well

known the Order’s principles become, consumers and business

clients may also start to expect AI designers to incorporate the

Order’s principles into the development of private-sector AI.

Although I respect the need to apply the principles above on

a case-by-case basis, I hope that the Biden administration lifts its

eyes to see the forest for the trees, moving beyond imposing prin-

ciples on the development of AI regulations and applications to the

impact those regulations and applications have in the world.Will

Americans experience less discrimination because of AI? WillAI

materially improve their economic status or quality of life? Will

they feel they have more oversight of the forces in their lives

because of AI? These are the big picture questions that lawmakers

and policymakers should be forced to consider when adopting AI

regulations and applications.

Timelines for Federal AI Actions

The Order also sets deadlines for certain AI actions by the

federal government, including:

1. June 1, 2021 (180 days aer the date of the order)—e

Director of OMB shall publicly post a “roadmap for the

policy guidance that OMB intends to create or revise” to

support the use of AI by the federal government.

2. February 1, 2021 (60 days aer the date of the order)—

e Federal Chief Information Ocers Council (“CIO

Council”) shall “identify, provide guidance on, and make

publicly available the criteria, format, and mechanisms for

agency inventories of non-classied and non-sensitive use

cases of AI by agencies.”

3. Within 180 days of the CIO Council completing its task

in #2 above, each federal agency shall prepare an inven-

tory of its non-classied and non-sensitive use cases of

AI, including current and planned uses.

4. Within 120 days of completing its inventory, each agency

shall “develop plans either to achieve consistency with this

order for each AI application or to retire AI applications

230 e Journal of Robotics, Articial Intelligence & Law [4:227

found to be developed or used,” and the relevant ocial

shall approve those plans within the same 120-day peri-

od.

Agencies shall aim to implement their plans within

180 days aer approval.

5. Within 120 days of completing its inventory, each agency

shall make its inventory available to the public, as permit-

ted by law and policy.

Assuming that these timelines are not changed by future execu-

tive orders and the agencies are able to hold to the prescribed sched-

ules (a big assumption), we will know substantially more about how

the federal government currently uses AI, how it plans to use AI,

and how federal agencies will consider future AI applications. This

could have major implications on (i) private development of AI, as

private companies shift their research and development strategies

to appeal to federal customers, and (ii) individuals who interact

with the federal government, as they may have a better idea of the

AI resources available to them in those interactions.

Deﬁnition of AI

There is a persistent debate in technical and legal circles about

how to define AI. It can be difficult to find consensus regarding

the qualities necessary for an application or device to qualify as AI.

There is also a sliding scale that the industry constantly encounters;

as one expert laments, “[a]s soon as it works, no one calls it AI

a ny m o r e .”

In legal documents and contracts, this debate manifests

itself by the parties having competing interests dictating how spe-

cifically or broadly to define AI. A party that is obligated to make

representations concerning its AI, or to perform certain training

or diagnostics, is incentivized to make the contractual language

of AI narrow, possibly naming specific applications in the defini-

tion. On the other hand, a party that is relying on a contractor’s

AI to provide services wants to ensure all the AI applications are

trustworthy and unbiased, meaning it wants the definition of AI

to be as broad as possible.

The Order continues the trend of federal statutes, regulations,

and orders relying on the definition of AI in Section 238(g) of the

John S. McCain National Defense Authorization Act for Fiscal Year

2019 (the “McCain Act”). Per that section, AI includes any of the

following:

2021] e Federal Government and Trustworthy AI 231

■ Any articial system that performs tasks under varying and

unpredictable circumstances without signicant human

oversight, or that can learn from experience and improve

performance when exposed to data sets.

■ An articial system developed in computer soware, physi-

cal hardware, or other context that solves tasks requiring

human-like perception, cognition, planning, learning,

communication, or physical action.

■ An articial system designed to think or act like a human,

including cognitive architectures and neural networks.

■ A set of techniques, including machine learning, that is

designed to approximate a cognitive task.

■ An articial system designed to act rationally, including an

intelligent soware agent or embodied robot that achieves

goals using perception, planning, reasoning, learning,

communicating, decision making, and acting.

That is a broad definition of AI. If federal law continues to rely

on this definition, that could influence how contractual language

defines AI between private parties.

Conclusion

With the impacts described above in mind, AI developers

should start considering how to incorporate the Order’s principles

and the McCain Act’s definition of AI into their research and devel-

opment processes. Whether they market to governments, private

companies, or consumers, that definition and those principles are

likely to emerge as the industry’s best practices and the regulatory

standards.

Having said that, there still remains a void regarding value-

based guidance for the end results of AI. What do we want that to

look like? Some of the principles in the Order and the OMB Memo

are desirable in AI—we want AI to be safe, accurate, etc.—but

what do we want the world with AI to look like? Should AI make

the world less discriminatory? Should it promote the value of

human labor? If AI applications will be as revolutionary as some

people in the sector believe, federal regulations and adoption

of AI should be based more on the principles of the evaluator

process, but also on the values of the outcome. That AI would be

genuinely trustworthy.

232 e Journal of Robotics, Articial Intelligence & Law [4:227

Notes

* John Frank Weaver, a member of McLane Middleton’s privacy and data

security practice group, is a member of the Board of Editors of e Journal

of Robotics, Articial Intelligence & Law and writes its “Everything Is Not

Terminator” column. Mr. Weaver, who may be contacted at john.weaver@

mclane.com, has a diverse technology practice that focuses on information

security, data privacy, and emerging technologies, including articial intel-

ligence, self-driving vehicles, and drones.

1. Exec. Order No. 13,960, 85 Fed. Reg. 78939 (December 3, 2020), avail-

able at https://www.federalregister.gov/documents/2020/12/08/2020-27065/

promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-

government (the “Order”).

2. Id., at Sec. 1.

3. Exec. Order No.13,859, 84 Fed. Reg. 3967 (February 14, 2019), avail-

able at https://www.federalregister.gov/documents/2019/02/14/2019-02544/

maintaining-american-leadership-in-articial-intelligence; see John Frank

Weaver, “Everything Is Not Terminator: What Does the Executive Order

Calling for Articial Intelligence Standards Mean for AI Regulation?,” e

Journal of Articial Intelligence & Law (Vol. 2, No. 5; September-October

2019), 373-379.

4. Oce of Management and Budget Memorandum, Guidance for

Regulation of Articial Intelligence Applications (November 17, 2020), avail-

able at https://www.whitehouse.gov/wp-content/uploads/2020/11/M-21-06

.pdf (“OMB Memo”).

5. Id., at 3-7. e OMB Memo’s conation of regulatory and non-

regulatory approaches to governing AI is problematic, as it could limit the

federal government’s ability to make qualitative decisions about outcomes and

benets concerning AI and slow down needed AI regulation. See John Frank

Weaver, “Everything Is Not Terminator: e White House Memo on Regulat-

ing AI Addresses Values but Not the Playing Field,” e Journal of Articial

Intelligence & Law (Vol. 3, No. 3; May-June 2020) (describing how the dra

memo predating the OMB Memo overemphasizes growth and innovation at

the expense of the government’s ability to timely and eectively regulate AI).

6. Order, supra note 1, at Sec. 3.

7. See John Frank Weaver, “Everything Is Not Terminator: Value-Based

Regulation of Articial Intelligence,” e Journal of Articial Intelligence &

Law (Vol. 2, No. 3; May-June 2019), 219-226 (“We need to regulate AI now

in order to set early expectations for AI developers: what should consumers

reasonably expect, what processing behavior is acceptable, what information

must be disclosed, etc.”).

8. Order, supra at note 1, at Sec. 4(b).

9. Id., at Sec. 5(a). As of the writing of this article, the CIO Council

has missed this deadline and has not produced the required guidance and

information.

2021] e Federal Government and Trustworthy AI 233

10. Id., at Sec. 5(b).

11. Id., at Sec. 5(c)(i).

12. Id., at Sec. 5(c)(ii).

13. Id., at Sec. 5(e).

14. Moshe Y. Vardi, “Articial Intelligence: Past and Future,” Communica-

tions of the Association for Computing Machinery (Jan. 2012), 5, at 5.

15. See John Frank Weaver, “Everything Is Not Terminator: Dening

AI in Contracts,” e Journal of Articial Intelligence & Law (Vol. 3, No. 6;

November-December 2020), 435-441 (“where the contract governs a rela-

tionship in which one or more parties may or may not rely on AI, dening

what the contract will consider and treat as AI may be heavily negotiated”).

16. John S. McCain National Defense Authorization Act for Fiscal Year

2019, Pub. L. No. 115-232, §238(g) (2019).