Comments of the Recording Industry Association of America on the National Institute of 

Standards and Technology Request for Information Regarding the Artificial Intelligence Risk 

Management Framework

Docket No. 210726-0151

Delivered via email to aiframework@nist.gov

September 15, 2021

The Recording Industry Association of America (“RIAA”) welcomes this opportunity to respond 

to some of the questions posed by the National Institute of Standards and Technology (“NIST”) 

in its request for information (“RFI”)1regarding the Artificial Intelligence Risk Management 

Framework (“AI RMF”).

The RIAA is the trade organization that supports and promotes the creative and commercial 

vitality of music labels in the United States, the most vibrant recorded music community in the 

world. Our membership – which includes several hundred companies, ranging from small-tomedium-sized enterprises to global businesses – creates, manufactures and/or distributes 

sound recordings representing the majority of all legitimate recorded music consumption in the 

United States. In support of its mission, the RIAA works to protect the intellectual property and 

First Amendment rights of artists and music labels; conducts consumer, industry, and technical 

research; and monitors and reviews state and federal laws, regulations, and policies.

Introduction

Human creative expression is at the core of our members’ businesses and is vital to our nation’s 

culture and economy. The United States boasts over one million revenue-generating sound 

recording artists and songwriters.

2

 Overall, the music industry contributes $170 billion to the 

nation’s economy, supports 2.47 million jobs and accounts for over 236,000 businesses in the 

United States.3 At the core of all this activity is the creativity of sound recording artists, 

songwriters, musicians, producers, recording engineers and countless other participants in the 

music industry that bring music to life. Their creative output is protected by copyright, which is 

1

 86 Fed. Reg. 40,810 (July 29, 2021).

2

Source: http://50statesofmusic.com/?USimpact. 

3

Source: http://50statesofmusic.com/?USimpact. 
both recognized in the U.S. Constitution4 and in the U.N. Universal Declaration of Human 

Rights.5

The process of making the music we describe above is full of experimentation, innovation, and 

technological experimentation. Our members are constantly working with artists to develop 

and use new tools and techniques to spark their creativity, hone their sound, and better engage 

with music fans. It is in this light, and in consideration of how the AI RMF relates to the 

creation, use, and exploitation of music, that we offer the following comments.

Transparency, Fairness and Accountability.

We appreciate that the aim of the AI RMF is to “cultivate the public’s trust in the design, 

development, use and evaluation of AI technologies and systems in ways that enhance 

economic security, and improve quality of life.”6 As NIST has stated, to meet that goal, the AI 

RMF should encompass principles of transparency, fairness, and accountability.7 

Licensing and Clearances. To promote these principles, the AI RMF should encourage AI 

developers to use only those training materials for which the AI developer has received 

appropriate licenses or clearances for the reproduction or other exploitation of those materials

or those training materials that are in the public domain. The AI RMF should discourage the use 

any copyrighted materials for training unless the AI developer has received the appropriate 

licenses or clearances. Wholesale copying of sound recordings merely for the purpose of 

“training” an AI system, without more, is an insufficient basis for a finding of fair use, much like 

wholesale copying for the training of human students is not fair use.8 As courts have found, 

where a use would not constitute fair use when done in the physical world, it does not 

constitute fair use on the Internet.

9

 Similarly, where wholesale copying would not be 

considered fair use for teaching humans when performed with older technologies, it should not 

be considered fair use later when done to “teach” an algorithm with newer technologies. 

Accordingly, and to avoid harm to rights holders and mitigate the risk to AI developers, the AI 

4 U.S. Const. art. 1, § 8, cl. 8 (“To promote the Progress of Science and useful Arts, by securing for limited Times to 

Authors and Inventors the exclusive Right to their respective Writings and Discoveries;”).

5

 art. 27, § 2 (“Everyone has the right to the protection of the moral and material interests resulting from any 

scientific, literary or artistic production of which he is the author”).

6

 86 Fed. Reg. at 40,811 (July 29, 2021).

7

Id.

8

See e.g. Blackwell Publ’g, Inc. v. Excel Research Grp., LLC, 661 F. Supp. 2d 786 (E.D. Mich. 2009) (third party 

copying copyrighted content in course packs without authorization to sell them to students not fair use); Am. 

Geophysical Union v. Texaco, Inc., 60 F.3d 913 (2d Cir. 1995) (copying of articles by researchers beyond what was 

permitted in the license for the articles was not fair use); Weissmann v. Freeman, 868 F.2d 1313 (2d Cir. 1989) 

(professor’s unauthorized copying and distribution of a copyrighted article to his students not fair use); Educ. 

Testing Serv. v. Katzman, 793 F.2d 533 (3d Cir. 1986), abrogated on other grounds by eBay, Inc. v. MercExchange, 

LLC, 547 U.S. 388 (2006) (copying of a copyrighted test for test preparation education not fair use).

9 Brammer v. Violent Hues Prods., LLC, 922 F.3d 255, 269 (4th Cir. 2019) (“Such a use would not constitute fair use 

when done in print, and it does not constitute fair use on the Internet.”).
RMF should promote as a best practice that AI developers obtain licenses or other clearance to 

use any copyrighted training materials, or that they instead rely on public domain materials.10

Record keeping. In addition, the AI RMF should call on AI developers to maintain adequate 

records of what copyrighted works or other materials are being ingested by the AI process and 

for what purposes, copies of the licenses or clearances the developer has obtained to use the 

works or materials for such purposes, and what are the outputs of the AI process. Because AI 

ingestion or “training” will typically not happen in the public eye, it will be difficult if not 

impossible for copyright owners to monitor the unauthorized use of their intellectual property

without such records. Proper record keeping of what content was ingested as part of the AI 

process should help ensure transparency and enhance accountability. In addition, such record 

keeping with respect to the licenses or clearances obtained will act as a check against rampant 

infringement in connection with AI inputs. It also can help track potentially problematic AI 

outputs, such as “deep fakes” or other outputs that may infringe intellectual property rights. 

This will help ensure fairness and build trust.

* * *

We thank NIST for the opportunity to share these preliminary views on what should be included 

in the AI RMF. We look forward to continuing this conversation with NIST and other policy 

makers as AI technology and its impact on the marketplace and society evolves.

10 NIST should be wary of making any recommendations concerning the use of training materials under the fair use 

doctrine. The fair use doctrine is a fact-intensive inquiry that requires a deliberative analysis under the four factors 

for fair use set forth in 17 USC § 107. Therefore, relying on fair use should not be taken lightly or without a full 

grasp of the relevant facts for each particular situation.