JAPAN INTELLECTUAL PROPERTY ASSOCIATION
Nihombashi 3-Chome Square Bldg.
6F, 9-1 Nihonbashi 3-chome,
Chuo-ku, Tokyo 103-0027, JAPAN

TEL:+81-3-6262-1570
FAX:+81-3-6262-5655
URL:http://www.jipa.or.jp/

Oct 30th ,2023
Dr Shira Perlmutter
Register of Copyrights and Director, U.S. Copyright Office
101 Independence Ave. S.E.
Washington, D.C.
20559-6000
Dear Dr Shira Perlmutter,
Re: Request for comment on Artificial Intelligence and Copyright by U.S.
Copyright OfficeWe, the Japan Intellectual Property Association “JIPA”, are a private userorganization with about 990 major Japanese companies as members. Whenappropriate opportunities arise, we offer our opinions on the intellectual
property system of other countries and make recommendations for more
effective implementation of the systems.
Having learned a request for comment on Artificial Intelligence andCopyright on your website, we would like to offer our opinions as follows.
Your consideration on our opinions would be greatly appreciated.
Sincerely yours,

Toru ItoManaging Director
Japan Intellectual Property Association

JIPA Comment:
4. Are there any statutory or regulatory approaches that have been adopted
or are under consideration in other countries that relate to copyright and AI
that should be considered or avoided in the United States? How important afactor is international consistency in this area across borders?
In Japan, issues regarding copyright and AI are sorted out into "(1) learning
phase" and "(2) use phase”, in order to elaborated the discussion.
As for (1) the learning phase, when the use the work is deemed to be not for
purpose of enjoyment, the use of copyrighted works t is organized to besubject to restrictions on rights to the extent necessary, unless it does notunreasonably prejudice the benefits of rightsholders.
In addition,(2) in the use phase, "reproduction" applicability (judgement
regarding "basis" that is a requirement for the authorization of reproduction)is particularly problematic when copyrighted works similar to those inlearning datasets are output in a way unintended by a developer or a user.
We believe that sorting the issues into those phases is also effective in theUnited States.
5. Is new legislation warranted to address copyright or related issues withgenerative AI? If so, what should it entail?
(Although this not only can be said for this question but also for multiple
questions below relating to whether laws and regulations need to bedeveloped,)
As AI is a rapidly changing area , it is desirable to strike a balance between
protection and use. by focusing more on soft law (for example, measures byguidelines) that can be flexibly implemented,or by architecture(implementation of opt out based on the rightsholder’s will, and mechanisms
to prevent output of content similar to that of others, and the like usingtechnology) rather than hard law that requires time for enactment andenforcement.
9.2. If an ‘‘opt out’’ approach were adopted, how would that process work fora copyright owner who objected to the use of their works for training? Are
there technical tools that might facilitate this process, such as a technicalflag or metadata indicating that an automated service should not collect andstore a work for AI training uses?
9.3. What legal, technical, or practical obstacles are there to establishing orusing such a process? Given the volume of works used in training, is it
feasible to get consent in advance from copyright owners?
(To answer 9.2 and 9.3 collectively),For websites, it is possible to disallow
crawling on one's own site for certain or all crawlers by utilizing a disallow
tag of robot.txt, and this is conceived to function to a certain extent as an opt
out by the rightsholder. However, it should be noted that (1)the web site
installer are not necessarily the same as the rightsholder, (2)robot.txt isoriginally created to manage crawling for the purpose of search and basically-1-

cannot distinguish crawling for the purpose of search and crawling for thepurpose of machine learning from each other,(3) disallow for all crawlers
would also disqualify the site from search,(4)the legal assessment without
regard to robot.txt is unclear, and (5) the introduction of new opt-out
mechanisms specific to machine learning is subject to a major global
standardization effort.
10.1. Is direct voluntary licensing feasible in some or all creative sectors?
Since there is no one-size-fits-all approach to generative AI, and various
legal risks may be taken into account in some cases depending on the specificcontent of the AI learning model and interpretation of copyright law, webelieve that legal safety for the user and an appropriate return ofcompensation to the rightsholder can be balanced by a licensing scheme of
the rightsholder.
Where the rightsholder voluntarily provides a licensing scheme underreasonable conditions, no rights limitations are applied (Fair Use is notapplied) to use that may harm the market of the license, and the user needs
to get permission from the rightsholder. especially in the case of fine tuning,where there may be inherent high value in the work being learned, thelicense scheme may provide the rights holder with an appropriate return ofconsideration.
As this issue is an area where the interpretation of copyright law isinvolved in the effectiveness of the licensing scheme, accumulation of judicial
precedents and discussions regarding legal interpretation are awaited first.
In any case, whether the rightsholder wants such license needs to be
examined for each type of content.
15. In order to allow copyright owners to determine whether their works
have been used, should developers of AI models be required to collect, retain,
and disclose records regarding the materials used to train their models?
Should creators of training datasets have a similar obligation?
While it is important to respect the rights of creators in the first place, acompany that performs fine tuning of a foundation model, for example, may
input content that falls under trade secrets. In addition, the type of data
used for learning itself may have commercial value, and hence it isimportant to appropriately protect such values that should be kept safe bycompanies from the standpoint of appropriately facilitating corporateactivities.
22. Can AI-generated outputs implicate the exclusive rights of preexisting
copyrighted works, such as the right of reproduction or the derivative work
right? If so, in what circumstances?
We believe that at least those generated with AI by a user intentionallytrying to create something similar to certain copyrighted works can conflictwith the right of reproduction, the derivative work right, and the like and-2-

infringe rights unless rights limitation provisions are applied. Meanwhile, it
is debatable whether those works conflict with such rights, when copyrighted
works similar to those in datasets for learning are output in a way
unintended by a developer or a user.
In Japan, in order to conflict with the right of reproduction and thederivative work right, the copyrighted work of concern requires to be createdon the "basis" of the original copyrighted work, but in what cases areunderstood to be the "basis" (whether the internal intention of use of theuser is a requirement or whether a conflict with the right of reproduction
and the like occurs on the "basis" of datasets for learning when there aresimilar works in the datasets for learning and those works are used, andwhat "use" means in that case) is under consideration by the government.
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